MCP Server

Analytics Legends — SAP Analytics Intelligence

ai.analyticslegends/sap-analytics
Data & Analytics Education Search & Research Public & reachable MCP 2025-11-25

What this MCP does

Provides SAP analytics intelligence through searchable firm, market, opportunity, news, concept, study, training, and knowledge-graph data.

count_firms_by
Count the firm directory by country, kind, module or SAP signal
Answer a COUNTING question about the published firm directory in one call: how many organisations per country, per kind, per declared SAP module, or per SAP signal band — with the same `country`/`kind`/`module`/`query` filters `search_firms` takes, so you can count a slice as easily as the whole. Use this instead of paging `search_firms` and tallying rows: the directory holds thousands of organisations, and reading them all to produce a table of counts costs hundreds of calls and megabytes of rows for numbers Postgres computes in one scan. Every bucket is a value the directory actually stores; `value: null` is a real bucket meaning the field is unknown for those rows, and it is served rather than hidden — a country table that silently drops the rows with no country adds up to less than the population and says nothing about it.
Read only Idempotent
Input schema
{'type': 'object', 'required': ['by'], 'properties': {'by': {'enum': ['country', 'kind', 'module', 'sap_signal_band'], 'type': 'string', 'description': 'Which facet to count on. Required — there is no default worth guessing.'}, 'kind': {'type': 'string', 'description': 'Restrict to one organisation kind before counting, same vocabulary as search_firms. Combining it with `by:"kind"` is legal and returns that single bucket.'}, 'query': {'type': 'string', 'maxLength': 200, 'description': 'Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.'}, 'module': {'type': 'string', 'description': 'Restrict to organisations with a DECLARED link to one SAP module code before counting, same vocabulary as search_firms\' `module`. Combining it with `by:"module"` is legal and returns that single bucket (plus the null bucket).'}, 'country': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': 'ISO-3166-1 alpha-2 country code, e.g. DE, FR, CH.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'n': {'type': ['integer', 'null']}, 'value': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
find_academy_modules
Search the Academy training catalogue
Search the Analytics Legends Academy — the written training modules on SAP Datasphere, Business Data Cloud, SAP Analytics Cloud, BW/4HANA and Databricks — by track, level and free text. `_meta.tranche_total_row_count` carries the live catalogue size on every call; it is the only count to quote. Returns the catalogue entry: id, slug, EN/FR title, track, level, duration in minutes, tags and the editor's summary. DO NOT CONFUSE IT WITH `list_sap_modules`, which serves a different population under the same word: that one is the 40-row PRODUCT taxonomy (codes such as SAC, DATASPHERE) used to normalise product wording. This one is the course catalogue. Without `query`, rows come back in the catalogue's own CURRICULUM order — the order a reader is meant to take them in — track by track. This catalogue is written training, NOT SAP certification tracks: this server publishes no certification data at any tier, so a certification question has no answer here rather than a partial one. CATALOGUE ONLY — the module BODY is subscriber content, served by `get_academy_module` on this same endpoint with a subscriber key (Consultant tier or above), which is the same door the €29.90 Consultant Pass opens on the site. On THIS endpoint the machine-access subscription is the MCP Pass (€39.90/month, analyticslegends.ai/pricing/), which opens the ENTIRE paid tranche from one key; the €29.90 Consultant Pass is its web-subscriber equivalent and opens the same tier floor here. `status` and `is_preview` are SERVED, never filtered on: they are the two flags the platform marks free access with, they do not coincide (measured 2026-08-16: 38 rows `status='available'`, 56 rows `is_preview`), and you decide which one your answer needs. PAGINATED: pass `_meta.next_cursor` back as `cursor` with the same filters until it is null. Read `_meta.available_tracks` and `_meta.available_levels` — both counted on the served population at call time — before assuming a facet value exists.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'level': {'type': 'string', 'description': 'Restrict to one level, matched case-insensitively: Beginner · Intermediate · Advanced · Expert. Counts in `_meta.available_levels`.'}, 'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'query': {'type': 'string', 'maxLength': 200, 'description': 'Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.'}, 'track': {'type': 'string', 'description': 'Restrict to one track, by SLUG (`databricks-data-eng`) or by English name (`Databricks & Data Eng.`), matched case-insensitively. The live vocabulary with per-track counts is `_meta.available_tracks` on every response. The numeric track_id is deliberately NOT accepted — it is an internal counter, and passing `6` would look like naming a subject.'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': ['string', 'null'], 'description': 'Module id, e.g. M001 — the value get_academy_module takes.'}, 'slug': {'type': ['string', 'null']}, 'tags': {'type': ['array', 'null'], 'items': {'type': 'string'}}, 'level': {'type': ['string', 'null']}, 'status': {'type': ['string', 'null'], 'description': "Editorial access marker: 'available' or 'legend-pass'. Served, not filtered on. READ 'legend-pass' AS 'sold at the CONSULTANT tier': it is a LEGACY label from when the paid tier was called Legend, it sits on the majority of rows, and the tier that actually opens the body here is Consultant (get_academy_module). The site stopped rendering this field for exactly that reason on 2026-07-26; this endpoint still serves the raw value, so the LABEL is the stale half and the tier floor is the true one."}, 'title_en': {'type': ['string', 'null']}, 'title_fr': {'type': ['string', 'null']}, 'is_preview': {'type': ['boolean', 'null'], 'description': 'The second free-access marker. Does NOT coincide with status — read both.'}, 'summary_en': {'type': ['string', 'null']}, 'summary_fr': {'type': ['string', 'null']}, 'track_slug': {'type': ['string', 'null']}, 'updated_at': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'track_name_en': {'type': ['string', 'null']}, 'track_name_fr': {'type': ['string', 'null']}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}, 'duration_minutes': {'type': ['number', 'null']}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
find_opportunities
Search the public SAP analytics contract radar
Search every SAP contract and permanent-role posting Analytics Legends publishes to an ANONYMOUS visitor — the same population a human browses on /opportunities/, where each posting has its own prerendered page. It merges the platform's TWO public legs, which are near-disjoint (measured 2026-07-30: 1 row in common): (a) the PROMOTED feed (`public.public_opportunities`) — general SAP work (FI/CO, SD, EWM, MDG, BTP, ABAP), all German cities, dated (posted_at is populated on EVERY active row of that leg — an invariant held since 2026-07-31, not a snapshot). 🔴 THIS LEG CHANGED SHAPE ON 2026-08-28: until then it was fed by three keyless APIs and carried no contract_type, country_code, expires_at or rate at all; it was then loaded from the site radar and now declares contract_type and country_code on most of its rows, an expiry on most, and an advertised rate on a small minority. Do NOT assume a field is null on this leg — read the `_meta` counters on YOUR OWN response, which are computed at query time; (b) the SITE RADAR (`/api/contracts-lean.json`) — these carry country, category, seniority, posted_at, `employment_type` and, on most of them, `expires_at`; they are the analytics-specific ones (SAC Planning, Datasphere Technical Lead, Business Data Cloud). READ `employment_type` BEFORE CALLING THIS A CONTRACT MARKET: the radar is mostly PERMANENT roles, so an unfiltered page answers a freelance question with salaried jobs unless you filter. The argument of the same name does the filtering, and `_meta.tranche_total_row_count` on your own response is the live population — read the split from a filtered call, never from a figure quoted in this text. TWO DIFFERENT RATE FIELDS, AND THEY MEAN DIFFERENT THINGS. `currency` / `daily_rate_min` / `daily_rate_max` are the posting's OWN advertised rate and are almost always null — most listings publish no rate at all. `rate_band` is the platform's editorial benchmark for that posting's (seniority × product × region) cell, present on most rows, and it is what the posting's public page leads with. It is `rate_basis: "panel_inferred"` — Eursap n=312 plus the Analytics Legends operator panel, permanent rows restated as a TJM equivalent at ~220 billable days a year — NOT a rate this employer offered. Quote it as a band with its `basis`, `kind` and `source`, never as the posting's rate, and never average bands across postings: many rows share one cell. WHAT IS GATED IS A FIELD, NOT A ROW: on most radar rows `source_url` is null and `application_link` reads "members_only" — the verified link to the original listing is the paid Consultant-tier deliverable. Everything else about the posting is public, and `citation_url` is that posting's own page on analyticslegends.ai. Quote it. Report `_meta.tranche_row_count` as the published public population, never as the size of the market.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'lang': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': "Reading language for the TITLE — 'EN' (default), 'FR' or 'DE'. This is a RENDERING choice, never a filter: it changes which string `title` carries, never which rows come back. Read `title_lang` on every row for the language actually served: it differs from what you asked for exactly when that translation does not exist (FR covers 1,492 of 1,588 site-radar rows, DE 1,373 — measured 2026-09-04), and the verbatim is served instead, labelled with the language the harvest chain measured. `source_lang` always carries the language the ADVERTISER wrote in, translated or not. The promoted leg has no translated columns at all: its rows ignore this argument and say so with `title_lang: null` — see `_meta.untranslated_leg`."}, 'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'query': {'type': 'string', 'maxLength': 200, 'description': 'Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}, 'country': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': "ISO-3166-1 alpha-2 code, applied to both legs as a predicate on the row's own country_code. It NO LONGER selects the site-radar leg alone: the promoted feed carried country_code on almost none of its rows until 2026-08-28 and now carries it on most, so a country filter now returns both legs. A row still without one is dropped because it does not match, not because its leg was excluded by assumption. `_meta.match_count_by_leg` shows what each leg contributed on YOUR call — read the split there, never from a figure quoted in this text."}, 'location': {'type': 'string', 'description': "City or place, matched case-insensitively as a substring of the posting's location. The promoted leg is all-German (Hamburg, Frankfurt am Main, Bremen, Munich, Cologne, Dortmund, Hanover, Landshut, Mannheim, Stuttgart); the site-radar leg is worldwide."}, 'remote_mode': {'type': 'string', 'description': "Restrict to one work-location policy: `remote`, `hybrid` or `onsite`. READ THIS BEFORE ANSWERING A REMOTE QUESTION: a large share of the radar declares no policy at all (`_meta.remote_mode_undeclared` carries the live count — roughly half the radar when last measured, and a frozen pair written here drifted ~30% in two days), and an undeclared row is NOT an on-site row — it is a posting that does not say. Any value here therefore sets those rows aside rather than classifying them, exactly as the site's own filter does, and `_meta.remote_mode_undeclared` reports how many were set aside. The promoted leg carries its own `remote_mode` column and is filtered by the same predicate. Read `_meta.available_remote_modes` for the live spread before assuming a value exists."}, 'employment_type': {'enum': ['freelance', 'contract', 'permanent'], 'type': 'string', 'description': 'Restrict to one engagement type. THE RADAR IS MOSTLY PERMANENT, so a freelance or contract question answered off an unfiltered page is answered with salaried jobs. For the actual split, make the filtered call and read `_meta.tranche_total_row_count` — it is counted at query time. The promoted leg declared NO contract_type until 2026-08-28 and now declares one on most of its rows, so a value here no longer drops that leg wholesale — only the rows still silent. THOSE ROWS ARE NOT A FOURTH TYPE AND NOT PERMANENT ONES: `_meta.available_employment_types` counts only what declares, and `_meta.employment_type_undeclared` carries the rest, so the two together are the population and either alone is not. Read both before quoting a mix.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': ['string', 'null'], 'description': "The posting's identity — stable across calls, key for dedup."}, 'leg': {'type': ['string', 'null'], 'description': '`promoted` or `site_radar` — which of the two merged public legs served this row.'}, 'title': {'type': ['string', 'null']}, 'skills': {'type': ['array', 'null'], 'description': 'Skills the posting names. Null when it names none.'}, 'source': {'type': ['string', 'null']}, 'category': {'type': ['string', 'null']}, 'currency': {'type': ['string', 'null']}, 'location': {'type': ['string', 'null']}, 'firm_name': {'type': ['string', 'null']}, 'posted_at': {'type': ['string', 'null']}, 'rate_band': {'type': ['object', 'null'], 'description': "Editorial benchmark for this posting's (seniority × product × region) cell — NOT a rate the employer offered. `basis` and `kind` are inside the object on purpose, so no extraction can lift the numbers away from what they mean. 2026-08-29: this band is a SUBSCRIBER surface and is no longer carried by the public radar file this lane reads — expect it to be null here. The posting's OWN published rate, when it has one, stays in currency / daily_rate_min / daily_rate_max."}, 'seniority': {'type': ['string', 'null']}, 'expires_at': {'type': ['string', 'null']}, 'salary_max': {'type': ['number', 'null']}, 'salary_min': {'type': ['number', 'null']}, 'source_url': {'type': ['string', 'null']}, 'title_lang': {'type': ['string', 'null'], 'description': "ISO-639-1 language the SERVED `title` is written in. READ IT ON EVERY ROW: it is what you asked for in `lang` when that translation exists, and the advertiser's own language when it does not (FR covers 1,492 of 1,588 site-radar rows, DE 1,373 — measured 2026-09-04). Null when the harvest chain could not decide, and on every promoted-leg row, which carries no translated column at all. ⚠️ THIS FIELD CHANGED REFERENT ON 2026-09-04: until then it named the language the ADVERTISER wrote in — that fact now lives in `source_lang`. The two coincided while no translation was served and diverge from the first one that is."}, 'description': {'type': ['string', 'null'], 'description': 'Posting text, HTML stripped, clamped. Null on the radar leg.'}, 'rate_period': {'type': ['string', 'null']}, 'remote_mode': {'type': ['string', 'null'], 'description': "The posting's declared work-location policy (`remote` / `hybrid` / `onsite`). NULL means the posting does not say — never read it as on-site."}, 'source_lang': {'type': ['string', 'null'], 'description': "ISO-639-1 language the ADVERTISER wrote the title in, measured by the harvest chain and never changed by `lang` — 'en' on 1,566 rows, 'de' on 337 (2026-08-23). Null when the chain could not decide, and on the promoted leg. Compare it with `title_lang` to know whether the title you are quoting is the advertiser's own words or this platform's rendering of them: a harvested posting is a third party's text, and saying which of the two you are citing is the only honest way to quote it."}, 'citation_url': {'type': 'string'}, 'country_code': {'type': ['string', 'null'], 'description': "ISO-3166-1 alpha-2 of the posting's own country. Null on almost all of the promoted leg."}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}, 'daily_rate_max': {'type': ['number', 'null']}, 'daily_rate_min': {'type': ['number', 'null'], 'description': 'Only when the source declares a DAILY rate period — never converted from other periods.'}, 'duration_months': {'type': ['number', 'null']}, 'employment_type': {'type': ['string', 'null']}, 'application_link': {'type': ['string', 'null'], 'description': '`public` (source_url is served) or `members_only` (the link to the original listing is the paid Consultant-tier deliverable; the row and its facts stay public).'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
find_sap_clients
Search the SAP end-customer corpus (Legend tier)
Search the SAP END-CUSTOMER corpus — the companies that RUN SAP, not the firms that sell services (those are search_firms). This is the paid Legend+ dataset locked away from the public surface on 2026-07-08; it requires a subscriber API key, Legend tier or above. Verification status is SERVED, never silently filtered: `sap_client_verification_status` and `status` are columns on every row ('verified' on ~550 of ~21k rows), and you decide what standard of proof your answer needs. `product` filters on the detected-adoption flags every profile already carries (the `uses_*` columns get_sap_client_profile serves): it keeps only rows where that product was DETECTED. A row it drops is 'not detected by our detection pass', never 'does not use it' — detection is a positive signal with no negative counterpart.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'query': {'type': 'string', 'maxLength': 200, 'description': 'Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}, 'country': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': 'ISO-3166-1 alpha-2 country code, e.g. DE, FR, CH.'}, 'product': {'enum': ['datasphere', 'bdc', 'sac', 'bw', 'bw4hana', 's4hana', 'ecc', 'hana', 'joule', 'businessobjects', 'bpc', 'successfactors', 'ariba', 'concur'], 'type': 'string', 'description': 'Keep only end-customers where this SAP product was DETECTED in use. Absence from the result means undetected, not unused.'}, 'industry': {'type': 'string', 'maxLength': 200, 'description': 'Industry or sector filter, matched case-insensitively.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': ['string', 'null']}, 'name': {'type': ['string', 'null']}, 'industry': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'country_code': {'type': ['string', 'null']}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}, 'sap_client_verification_status': {'type': ['string', 'null']}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
get_academy_module
Read an Academy module (Consultant tier)
Read one Academy training module in full — body, learning objectives and summary, EN, FR and DE — the written course corpus the €29.90 Consultant Pass sells. On THIS endpoint the machine-access subscription is the MCP Pass (€39.90/month, analyticslegends.ai/pricing/), which opens the ENTIRE paid tranche from one key; the €29.90 Consultant Pass is its web-subscriber equivalent and opens the same tier floor here. Requires a subscriber API key (Authorization: Bearer alk_…), Consultant tier or above; without one this tool refuses and `find_academy_modules` keeps serving the catalogue. Takes the module id (`M001`) or its slug (`datasphere-foundations`), both matched case-insensitively — `find_academy_modules` returns both on every row, and `query_knowledge_graph` returns the same ids as `module:M001` node ids, so a graph walk now ENDS somewhere. Unlike `get_study`, the whole module is served in one call: the longest body measured is 17 865 characters, two orders of magnitude under the response ceiling, so sectioning it would cost the caller context without protecting anything.
Read only Idempotent
Input schema
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'string', 'description': 'Module id (`M001`) or slug (`datasphere-foundations`), verbatim from find_academy_modules.rows[].id / .slug.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': ['string', 'null']}, 'slug': {'type': ['string', 'null']}, 'body_en': {'type': ['string', 'null']}, 'title_en': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'objectives_en': {'type': ['array', 'null'], 'items': {'type': 'string'}, 'description': 'Learning objectives, one per element — a text[] column, not a paragraph.'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
get_concept
Concept metadata and editor's summary (public)
Fetch one concept entry by slug: title, category, level, tags and the editor's summary. Written by a named human editor, not generated. The card body, why-it-matters, key points and pro tip are subscriber content and are NOT returned — follow citation_url for those.
Read only Idempotent
Input schema
{'type': 'object', 'required': ['slug'], 'properties': {'slug': {'type': 'string', 'description': 'Concept slug from search_concepts.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'slug': {'type': ['string', 'null']}, 'title': {'type': ['string', 'null']}, 'summary': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
get_concept_card
Full concept card (Consultant tier)
The FULL encyclopaedia card for one concept — body, why-it-matters, key points, cheat sheet, glossary, pro tip, and the four analysis tables (decision table, peer comparison, named pitfalls, performance facts), EN, FR and DE — the corpus the €29.90 Consultant Pass sells. On THIS endpoint the machine-access subscription is the MCP Pass (€39.90/month, analyticslegends.ai/pricing/), which opens the ENTIRE paid tranche from one key; the €29.90 Consultant Pass is its web-subscriber equivalent and opens the same tier floor here. Requires a subscriber API key (Authorization: Bearer alk_…), Consultant tier or above; without one this tool refuses and get_concept keeps serving the public metadata. Find slugs with search_concepts.
Read only Idempotent
Input schema
{'type': 'object', 'required': ['slug'], 'properties': {'slug': {'type': 'string', 'description': 'Concept slug, verbatim from search_concepts.rows[].slug.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'slug': {'type': ['string', 'null']}, 'body_en': {'type': ['string', 'null']}, 'title_en': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
get_day_rate_benchmark
Public SAP analytics day-rate aggregate
The PUBLIC day-rate aggregate for SAP analytics freelance work: min/max daily rate by country, specialisation and seniority, each row carrying its own currency, source, source date and confidence. This is the free aggregate published at analyticslegends.ai/api/market-rates.json, and it is SMALL — a few dozen rows at most, every one of them a secondary source (a published market study or a job-board scan), and `sample_size` is null on most of them. NO COUNT IS WRITTEN HERE ON PURPOSE: `_meta.tranche_total_row_count` and the rows themselves are the live measure. A frozen pair stood here until 2026-08-27 — '11 rows on 2026-08-09 … sample_size null on 8 of them' — and the second half was WRONG (7 of 11) while the first was still right, which is the whole argument against writing either. NOTHING IS HELD BACK BEHIND IT: there is no paid counterpart to this aggregate. The community-contribution path exists (public.rate_contributions) but publishes nothing yet — v_community_rate_aggregates and v_rate_index are still empty, because a contributed rate only surfaces once a cell holds enough submissions to be reported without identifying anyone. So whatever percentile a source row happens to carry is served here, free, to everyone. The GB row carries a median, p10 and p90, and its own note says its min/max ARE the 25th and 75th percentiles. What is missing from this answer is missing from THIS aggregate; it is not a paid tier. THIS IS NOT THE ONLY RATE THE PLATFORM PUBLISHES, AND ON THE QUESTIONS THIS MARKET ASKS MOST IT IS THE THINNER ONE. `find_opportunities` returns a `rate_band` on most live radar postings — a panel-inferred P25–P75 band per (seniority × product × region) cell, Eursap n=312 plus the Analytics Legends operator panel, and it is what each posting's public page leads with. It prices exactly the cells this small aggregate cannot — Senior Datasphere DACH, Senior BDC DACH — where `specialisation:"bdc"` here returns nothing. When this tool comes back empty for a country × product, say the AGGREGATE holds no row and go read the radar band — do not report that the platform cannot price it. The two are different instruments: this one is a published market study, that one is an editorial benchmark attached to a live posting. Read `_meta.available_countries` / `available_specialisations` / `available_seniorities` — they are computed from the aggregate on every call — before concluding that a rate is unpublished, and quote each row with its own currency, its confidence and its source date.
Read only Open world Idempotent
Input schema
{'type': 'object', 'properties': {'country': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': 'ISO-3166-1 alpha-2 country code, e.g. DE, FR, CH.'}, 'seniority': {'type': 'string', 'description': 'e.g. senior, principal.'}, 'specialisation': {'type': 'string', 'description': "One of the codes the aggregate actually holds — analytics_all, bw, bw4hana, bw4hana_sac, sac, datasphere (2026-08-09; the live list comes back as `_meta.available_specialisations` on every call). They are NOT evenly spread across countries: DE holds analytics_all only, at three seniorities, and datasphere exists for FR alone, as a median with confidence 'low'. There is no bdc row and no joule row in THIS aggregate — but the platform does price BDC: `find_opportunities` carries a panel-inferred band on the live postings, €1,000–€1,400/day P25–P75 for Senior BDC on 52 German postings (2026-08-10). A code this aggregate does not hold returns 0 rows and the available codes; it never widens to a neighbouring band, and 0 here does not mean the platform is silent."}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'country': {'type': ['string', 'null']}, 'currency': {'type': ['string', 'null']}, 'seniority': {'type': ['string', 'null']}, 'sample_size': {'type': ['integer', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}, 'specialisation': {'type': ['string', 'null']}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
get_firm
Get one firm's published profile
Fetch one organisation from the published directory by its database slug (`rows[].slug` from search_firms, verbatim). Returns the same public fields plus `partnerships_declared`, the count of partnerships this directory records for the firm — 0 on ~97 % of rows (re-measured 2026-08-14 on the published tranche: 96,8 %), meaning none declared here, never that the firm has no partners. Does not return the paid firm-intelligence profile, contacts, or any person.
Read only Idempotent
Input schema
{'type': 'object', 'required': ['slug'], 'properties': {'slug': {'type': 'string', 'description': 'The DATABASE slug, taken verbatim from search_firms.rows[].slug. It is not always the web slug in citation_url: a minority of published rows carry a numeric firm id instead (365 of them on 2026-08-09 — the population is read at query time and returned as `_meta.tranche_total_row_count`, never written down here). get_firm{slug:"00393"} is GULP, whose page is /companies/gulp/. Deriving a slug from the citation URL fails on those rows, and deriving it from the NAME is not safe either; carry rows[].slug across instead. A slug this tool refuses is not proof the firm is absent from the market or even from the database — the published tranche is an editorial subset, and a row the editor has not published is refused here exactly as a wrong slug is.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'name': {'type': ['string', 'null']}, 'slug': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
get_firm_intel
Firm intelligence profile (Legend tier)
The paid intelligence profile of a services firm — SAP practice size and partner level, delivery flags per product, typical day rate and seniority, notable clients, analytics practice summary, and a LinkedIn company URL (present on ~71% of the corpus, re-measured 2026-09-05 on 9,104 profiles — it read ~39% from 2026-08-10 to 2026-09-05, i.e. a third of the corpus below the truth, because an enrichment pass filled the column and no reader of this sentence was told — glassdoor_rating, glassdoor_reviews_count and linkedin_followers are null on the entire corpus as of 2026-08-10, absence here is a data gap, not a signal). READ THE SPARSITY BEFORE QUOTING A ROW: on the 9,103 profiles measured 2026-08-23, `typical_day_rate_eur` is null on 78.0% and `sap_partner_level` on 85.7% — the two headline fields are the exception, not the rule, and a null means 'not researched', never 'no partner level'. Requires a subscriber API key, Legend tier or above. Person-shaped fields (contacts, founders, leadership, recruiters, postal addresses) are NEVER served by this endpoint at any tier — they remain behind the platform's signed-URL path. Search by name; the public directory (search_firms) is a different, wider population.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'mode': {'enum': ['freelance', 'permanent', 'subcontract'], 'type': 'string', 'description': 'Keep only firms whose profile declares this engagement mode (mode_freelance / mode_permanent / mode_subcontract). Same reading as `delivers`: declared-only.'}, 'name': {'type': 'string', 'maxLength': 200, 'description': 'Firm name, matched case-insensitively. Omit to browse the corpus by data completeness.'}, 'limit': {'type': 'integer', 'default': 3, 'maximum': 10, 'minimum': 1, 'description': 'Max rows (hard cap 10 — these rows are wide).'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}, 'country': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': 'ISO-3166-1 alpha-2 country code, e.g. DE, FR, CH.'}, 'delivers': {'enum': ['datasphere', 'bdc', 'sac', 'bw', 'bw4hana', 's4hana', 'ecc', 'hana', 'joule', 'businessobjects', 'bpc', 'successfactors', 'ariba', 'concur'], 'type': 'string', 'description': 'Keep only firms whose profile DECLARES delivery of this product (the `delivers_*` flags every row already carries). An undeclared flag drops the row: absence from the result means the profile does not declare it, not that the firm cannot deliver it.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'name': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}, 'firm_id_unique': {}, 'sap_partner_level': {'type': ['string', 'null']}, 'typical_day_rate_eur': {}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
get_sap_client_profile
One SAP end-customer profile (Legend tier)
The full profile of one SAP end-customer — SAP footprint (products in use, modules known), analytics solutions, identity and evidence fields. Requires a subscriber API key, Legend tier or above. `id` comes verbatim from find_sap_clients.rows[].id.
Read only Idempotent
Input schema
{'type': 'object', 'required': ['id'], 'properties': {'id': {'type': 'string', 'maxLength': 160, 'description': 'Profile id, verbatim from find_sap_clients.rows[].id.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'id': {'type': ['string', 'null']}, 'name': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}, 'sap_products_used': {}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
get_study
Read a study (Consultant tier)
Read one Analytics Legends study BODY — the paid text behind list_studies' metadata. Requires a subscriber API key, Consultant tier or above. Bodies run to 38k words and exceed the 256 KiB response ceiling, so this tool serves STRUCTURE first: called without `section` it returns the section list and the introduction; pass `section` (a heading from that list, matched case-insensitively) to read one section. Find slugs and languages with list_studies.
Read only Idempotent
Input schema
{'type': 'object', 'required': ['slug'], 'properties': {'lang': {'type': 'string', 'default': 'en', 'pattern': '^[A-Za-z]{2}$', 'description': 'ISO-639-1 language of the edition, e.g. en or fr. Defaults to en.'}, 'slug': {'type': 'string', 'description': 'Study slug, verbatim from list_studies.rows[].slug.'}, 'section': {'type': 'string', 'maxLength': 200, 'description': "A section heading from a previous call's `sections` list. Omit to get the list."}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'slug': {'type': ['string', 'null']}, 'title': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}, 'section_heading': {'type': ['string', 'null']}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
list_firm_kinds
List firm kinds with live counts
Breakdown of the published firm directory by organisation kind, with a live row count per kind. Use this before search_firms to know what the population actually is instead of guessing.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'n': {'type': ['integer', 'null']}, 'kind': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
list_freelance_platforms
List the CV/profile platforms a consultant can sign up on
The subset of the published directory where a consultant can CREATE A PROFILE — freelance marketplaces, job boards with candidate profiles, talent platforms and expert networks — each with its signup URL, an editorial confidence grade and the date it was assessed. This answers the entering-contractor's first practical question ('where do I register?') in one call. Everything here is also in search_firms — this tool adds the platform fields and the filter, never a wider population. `signup_url` is the platform's own page: it was verified on `assessed_at`, and a platform absent here is not proven to refuse signups — it is unassessed or unpublished.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}, 'country': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': 'ISO-3166-1 alpha-2 country code, e.g. DE, FR, CH.'}, 'platform_type': {'type': 'string', 'description': 'Restrict to one platform type, lowercase snake_case. The live vocabulary with counts is `_meta.available_platform_types` on every response — a well-formed unknown value returns no rows, it never widens the result.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'name': {'type': ['string', 'null']}, 'slug': {'type': ['string', 'null']}, 'confidence': {'type': ['string', 'null'], 'description': 'Editorial confidence in the signup assessment.'}, 'hq_country': {'type': ['string', 'null']}, 'signup_url': {'type': ['string', 'null'], 'description': "The platform's own signup/profile-creation page, verified on assessed_at."}, 'assessed_at': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'platform_type': {'type': ['string', 'null']}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
list_sap_modules
SAP analytics module taxonomy
The canonical SAP module/product taxonomy Analytics Legends classifies against (codes and EN/FR labels by category). Use it to normalise a user's loose product wording — 'SAC', 'Analytics Cloud', 'Datasphere' — onto the codes the other tools filter on.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'query': {'type': 'string', 'maxLength': 200, 'description': 'Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'code': {'type': ['string', 'null']}, 'category': {'type': ['string', 'null']}, 'label_en': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
list_studies
List the deep-research studies (metadata only)
List the Analytics Legends deep-research studies with their edition, as-of date, audience, word count and canonical URL. METADATA ONLY: study bodies are a paid Consultant-tier deliverable, served by `get_study` on this same endpoint with a subscriber key. Use this to tell a reader that a study exists and where to read it. ONE ROW IS ONE LANGUAGE EDITION, NOT ONE STUDY: each study is published in every language it has been translated into, so `_meta.tranche_total_row_count` counts editions and `_meta.distinct_studies` counts the works. `_meta.available_languages` gives the live per-language counts; each row carries its `editions` list. Pass `lang` to get one row per study.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'lang': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': 'ISO-639-1 language of the EDITION to list, e.g. en, fr or de — each study is published as one row per language. Omit it to see every edition of every study; the live list of languages actually present comes back as `_meta.available_languages` on every response. A well-formed code the corpus does not hold returns 0 rows.'}, 'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'query': {'type': 'string', 'maxLength': 200, 'description': 'Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'lang': {'type': ['string', 'null']}, 'slug': {'type': ['string', 'null']}, 'as_of': {'type': ['string', 'null']}, 'title': {'type': ['string', 'null']}, 'access': {'type': ['string', 'null']}, 'editions': {'type': ['array', 'null'], 'items': {'type': 'string'}}, 'word_count': {'type': ['integer', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
query_knowledge_graph
Traverse the learning knowledge graph
The RELATIONS between the platform's teaching objects — which Academy module teaches which concept, which study covers which module, what a concept relates to. THIS IS THE ONLY TOOL ON THIS SERVER THAT SERVES EDGES; the others serve rows. Ask it what connects to what, not what exists. SCOPE, AND IT IS NARROWER THAN 'the knowledge graph': it carries four node types — `concept`, `module`, `study`, `vendor` — and every edge whose BOTH endpoints are one of them. The whole graph holds twelve node types; the eight it does not carry are each either served by their own tool or named as not served at all, and `_meta.excluded_node_types` says which per type (consultant data is served at NO tier), so a missing type is a documented boundary and never a silent gap. Call it with `node_id` (e.g. `module:M178`, `concept:C001`, `study:ai-impact-2026-EN`) to walk one node's neighbourhood; with `node_type` and/or `query` to find a node id first. `edge_type` and `direction` narrow a walk. Read `_meta.available_edge_types` — computed from the served projection on every call — before assuming an edge type exists.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'lang': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': 'ISO-639-1 language for the LABELS — en, fr or de. Defaults to en. The fallback is declared and never silent: the language asked for, then English, then French, and `_meta.label_language_coverage` says on how many nodes each language is actually filled. Concept and module titles carry French; German arrives as the corpus is translated, and an untranslated node falls back rather than being hidden.'}, 'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'query': {'type': 'string', 'description': "Case-insensitive substring of a node's label. Applies to the NODE listing, not to a walk. Matched against the label SERVED, so it follows `lang`."}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}, 'node_id': {'type': 'string', 'description': "Fully-qualified node id, `<type>:<id>` — `module:M178`, `concept:C001`, `study:ai-impact-2026-EN`, `vendor:alteryx`. With it, rows are that node's EDGES (one row per neighbour). Without it, rows are NODES."}, 'direction': {'enum': ['from', 'to', 'both'], 'type': 'string', 'description': 'Which side of the edge `node_id` must sit on. Default `both`. Ignored without `node_id`, and the response says so rather than pretending it applied.'}, 'edge_type': {'type': 'string', 'description': 'Restrict a walk to one relation. The served projection carries FIVE — teaches · taught_by · covers · related · mentions — and this list is a HINT, not the authority: read `_meta.available_edge_types`, computed on every call. A four-name list stood here while the projection served five, so `mentions` was reachable and undocumented.'}, 'node_type': {'type': 'string', 'description': 'Restrict to one carried node type: concept · module · study · vendor. Read `_meta.available_node_types`.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'label': {'type': ['string', 'null'], 'description': 'In the language asked for when the node carries it, else the declared fallback — see `label_lang`.'}, 'node_id': {'type': ['string', 'null']}, 'direction': {'type': ['string', 'null'], 'description': '`out` = node_id → neighbour, `in` = neighbour → node_id. Walk rows only.'}, 'edge_type': {'type': ['string', 'null'], 'description': 'Present only on a walk (when `node_id` was given).'}, 'node_type': {'type': ['string', 'null']}, 'label_lang': {'type': ['string', 'null'], 'description': 'The language the served `label` is actually written in. It differs from the requested `lang` exactly when that translation does not exist.'}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
search_concepts
Search the SAP analytics concept encyclopaedia
Search the SAP analytics concept encyclopaedia — the vocabulary of the stack, written for practitioners. Returns slug, title, category, level, tags and the editor's summary. `level` is SPARSE — null on 108 of the 330 active rows, measured 2026-08-27 — and a null there means 'not graded', never 'Beginner'. These are the same fields `get_concept` returns for ONE slug. The card BODY (why-it-matters, key points, cheat sheet, the four analysis tables) is Consultant-tier: call `get_concept_card`.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'query': {'type': 'string', 'maxLength': 200, 'description': 'Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}, 'category': {'type': 'string', 'description': 'Concept category, matched case-insensitively as an exact value OR a prefix — so category:"datasphere" reaches \'Datasphere Core\'. The values are long human labels, not codes. DO NOT GUESS THEM FROM THIS TEXT: the live vocabulary with a row count per label comes back as `_meta.available_categories` on EVERY call, including a call that matched nothing. A list written here would say 14 labels with 2026-07-30 counts; the corpus holds 15 today, and five of those counts have moved. Read the envelope, not the prose.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'slug': {'type': ['string', 'null']}, 'title': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
search_firms
Search the SAP analytics firm directory
Search the published Analytics Legends directory of SAP analytics service providers — placement agencies, Big-4 and ESN practices, SAP vendors, platforms and community groups — by country, kind, declared SAP module and free text. Returns name, HQ country/city, website, careers URL and a one-line editorial claim. SAP END-CUSTOMER companies are NOT in this directory: they are a separate paid dataset, excluded here by the `is_client` FLAG — not by the `client_enterprise` kind code. The two are different columns, and where a row's flag and its kind label disagree in the SSOT it is the flag that decides what this tool serves, so read the flag's meaning into the answer and not the label's. PAGINATED: the whole matched set is reachable — pass `_meta.next_cursor` back as `cursor` with the same filters until it is null. When `query` is set, rows are ordered by how well the NAME matches it (exact, then prefix, then substring), and rows matching only the description come last; without `query` the order is the directory's own quality ranking.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'kind': {'enum': ['agency_placement', 'professional_services_big4', 'professional_services_esn', 'vendor_sap', 'vendor_partner', 'platform_marketplace', 'community_group', 'client_enterprise', 'other'], 'type': 'string', 'description': 'Restrict to one organisation kind. This list is the vocabulary the corpus holds today, not a frontier — call list_firm_kinds for the live one. A malformed code is refused; a well-formed code the corpus does not hold returns no rows. Neither case is silently ignored, and neither widens the result.'}, 'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'query': {'type': 'string', 'maxLength': 200, 'description': 'Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}, 'module': {'type': 'string', 'description': 'Restrict to organisations with a DECLARED link to one SAP module/product code (UPPERCASE snake_case, e.g. DATASPHERE, BDC, SAC, BW4HANA, S4HANA, JOULE — case-insensitive on input). The declared links are structured data, far more selective than free text: `count_firms_by {by:"module"}` gives the live vocabulary with counts. A minority of the directory declares any module at all, so this filter finds the DECLARED specialists — absence from the result means no declared link, never that the firm does not work on the module.'}, 'country': {'type': 'string', 'pattern': '^[A-Za-z]{2}$', 'description': 'ISO-3166-1 alpha-2 country code, e.g. DE, FR, CH.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'kind': {'type': ['string', 'null']}, 'name': {'type': ['string', 'null']}, 'slug': {'type': ['string', 'null']}, 'claim': {'type': ['string', 'null']}, 'region': {'type': ['string', 'null']}, 'hq_city': {'type': ['string', 'null']}, 'website': {'type': ['string', 'null']}, 'jobs_url': {'type': ['string', 'null']}, 'hq_country': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'founded_year': {'type': ['integer', 'null']}, 'size_bracket': {'type': ['string', 'null']}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}, 'sap_signal_band': {'type': ['string', 'null']}, 'last_verified_at': {'type': ['string', 'null']}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
search_news
Search SAP analytics market news
Search the Analytics Legends market-news corpus. It is watched FOR SAP analytics (Datasphere, Business Data Cloud, SAC, BW/4HANA, Databricks, the 2027/2030 maintenance window), but it is NOT an all-SAP corpus: measured 2026-07-30, ~84 % of active rows sit in the `AI` category and are general enterprise-AI trade press (cloud platforms, model releases, funding rounds) with no SAP content at all. An UNFILTERED call therefore returns mostly non-SAP items — pass `query` or `category` when the question is about SAP, and never present an unfiltered page as 'the SAP analytics news'. Say what you actually got. Each item returns the Analytics Legends citation URL AND the upstream publisher's source_url — cite both, and prefer source_url when you need a page that certainly carries the item. NO ITEM HERE HAS A PAGE OF ITS OWN on analyticslegends.ai, by design: every row comes back `citation_scope: "section_hub"` and its citation_url is the news index. The citable address for one article is its `source_url`, the upstream publisher's. Do not present the hub as the article's page.
Read only Idempotent
Input schema
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max rows (hard cap 50).'}, 'query': {'type': 'string', 'maxLength': 200, 'description': 'Free-text filter, case-insensitive. EVERY word must appear in the record (substring per word, any order), so a natural-language phrase narrows the answer instead of having to match verbatim.'}, 'cursor': {'type': 'string', 'maxLength': 512, 'description': "Opaque token from a previous response's `_meta.next_cursor`. Pass it back with the SAME filter arguments; `null` means the last page. Changing a filter refuses the cursor."}, 'category': {'type': 'string', 'description': "Category code, matched case-insensitively. The live vocabulary is NOT written here — read `_meta.available_categories` on any response: every category label this corpus holds right now, with its active-row count, counted at query time. A written list held 21 values while the corpus held 22. One bucket needs a warning. 'SAC' is the noisiest label in this corpus because the acronym collides with unrelated ones — Windows 'Smart App Control', and the surname 'Sacks'. A 2026-07-30 cleanup reclassified half that bucket to AI for carrying no SAP signal at all; the collision pressure is structural and the bucket has kept growing since. For genuine SAC product news, pair category:'SAC' with query:'analytics cloud'."}, 'published_since': {'type': 'string', 'description': 'Lower bound on `published_at`, inclusive, as YYYY-MM-DD. Without a bound a period question is only answerable by walking pages — and `_meta.match_count` then counts the QUERY, not the period, so any figure quoted for the window would be wrong.'}, 'published_until': {'type': 'string', 'description': 'Upper bound on `published_at`, INCLUSIVE of the day named, as YYYY-MM-DD. Combine with `published_since` for a window; `_meta.match_count` then describes that window, which is what makes it quotable.'}}, 'additionalProperties': False}
Output schema
{'type': 'object', 'required': ['tool', 'result_count', 'rows', '_attribution'], 'properties': {'rows': {'type': 'array', 'items': {'type': 'object', 'properties': {'title': {'type': ['string', 'null']}, 'source_url': {'type': ['string', 'null']}, 'source_name': {'type': ['string', 'null']}, 'citation_url': {'type': 'string'}, 'published_at': {'type': ['string', 'null']}, 'citation_scope': {'enum': ['record', 'section_hub'], 'type': 'string'}}}}, 'tool': {'type': 'string'}, '_meta': {'type': 'object'}, '_attribution': {'type': 'string'}, 'result_count': {'type': 'integer'}}}
Added
get_firm_intel
2026年9月11日0:30
Added
get_sap_client_profile
2026年9月11日0:30
Added
find_sap_clients
2026年9月11日0:30
Added
get_academy_module
2026年9月11日0:30
Added
get_study
2026年9月11日0:30
Added
get_concept_card
2026年9月11日0:30
Added
query_knowledge_graph
2026年9月11日0:30
Added
find_academy_modules
2026年9月11日0:30
Added
list_sap_modules
2026年9月11日0:30
Added
get_day_rate_benchmark
2026年9月11日0:30
Added
list_studies
2026年9月11日0:30
Added
get_concept
2026年9月11日0:30
Added
search_concepts
2026年9月11日0:30
Added
search_news
2026年9月11日0:30
Added
find_opportunities
2026年9月11日0:30
Added
list_freelance_platforms
2026年9月11日0:30
Added
list_firm_kinds
2026年9月11日0:30
Added
get_firm
2026年9月11日0:30
Added
count_firms_by
2026年9月11日0:30
Added
search_firms
2026年9月11日0:30