此 MCP 可以做什么
Searches a company's ingested code, Slack and documentation, provides cited answers and dependency impact analysis, and proposes actions for human approval.
功能
工具
12
工具
get_graph
Return the community/knowledge graph manifest for visualisation.
Useful when the calling agent wants the high-level structure of the
key's workspace (clusters, hub nodes, cross-references) rather than
the contents of any one page. Returns ``{nodes, edges, communities,
stats}`` â exact shape mirrors the ``/api/wiki/graph`` REST endpoint.
输入模式
{'type': 'object', 'title': 'get_graphArguments', 'properties': {}}
输出模式
{'type': 'object', 'title': 'get_graphDictOutput', 'additionalProperties': True}
get_page
Fetch a single wiki page from the key's workspace.
Args:
category: One of ``entities | concepts | people | decisions |
sources | flows | infrastructure | tickets``.
name: Page slug (without ``.md`` extension), as returned by
``list_pages`` / ``search_wiki``.
Returns ``{category, name, content}`` â ``content`` is the full
markdown body including YAML frontmatter. Returns ``{error: "..."}``
if the page doesn't exist.
输入模式
{'type': 'object', 'title': 'get_pageArguments', 'properties': {'name': {'title': 'Name', 'default': ''}, 'page': {'title': 'Page', 'default': ''}, 'path': {'title': 'Path', 'default': ''}, 'slug': {'title': 'Slug', 'default': ''}, 'title': {'title': 'Title', 'default': ''}, 'category': {'title': 'Category', 'default': ''}}}
输出模式
{'type': 'object', 'title': 'get_pageDictOutput', 'additionalProperties': True}
get_process_map
Return the "living map of how the company works" for the key's workspace.
A graph of process nodes (compiled skills), the external systems
they touch (GitHub, Slack, Jira, â¦), the wiki docs they were
derived from, and team groups â with derived_from / uses /
references edges. Use this when the agent wants the high-level
operational structure rather than one skill's steps.
输入模式
{'type': 'object', 'title': 'get_process_mapArguments', 'properties': {}}
输出模式
{'type': 'object', 'title': 'get_process_mapDictOutput', 'additionalProperties': True}
get_skill
Fetch one compiled skill by name (slug from ``list_skills``).
Returns ``{name, markdown, meta}`` â ``markdown`` is the full
agent-executable SKILL.md content (frontmatter + steps), ``meta``
is the parsed frontmatter. Includes an ``error`` key when the
skill doesn't exist (with the available names).
输入模式
{'type': 'object', 'title': 'get_skillArguments', 'required': ['name'], 'properties': {'name': {'type': 'string', 'title': 'Name'}}}
输出模式
{'type': 'object', 'title': 'get_skillDictOutput', 'additionalProperties': True}
impact
Compute the blast radius of changing ``target`` in the key's workspace.
Use this before editing code to see what a change ripples into:
direct callers/callees, every affected file, the affected tests, the
transitive dependency set, and example dependency paths with per-path
facts (hops, dependents at the endpoint, whether it lands in a test).
There is deliberately no risk score. There was one â thresholds on the
transitive count â and it was a verdict the caller could not check or
argue with. The counts it was computed from are all here; judge from
those.
Args:
target: A graph node id, wiki page name, file path
(``micrograd/engine.py``), or a function fqn (``engine.py::func``).
depth: How many hops to traverse the call graph (default 2).
Returns the impact dict â ``{target, label, found, direct_callers,
direct_callees, affected_files, affected_tests, transitive_nodes,
transitive_count, paths, path_facts}``.
输入模式
{'type': 'object', 'title': 'impactArguments', 'required': ['target'], 'properties': {'depth': {'type': 'integer', 'title': 'Depth', 'default': 2}, 'target': {'type': 'string', 'title': 'Target'}}}
输出模式
{'type': 'object', 'title': 'impactDictOutput', 'additionalProperties': True}
list_pages
List every wiki page the caller can see in the key's workspace.
Returns a list of ``{category, name, title}`` records â feed each
one to ``get_page`` to fetch the full markdown body. Use this first
when you want a directory view; for a specific question prefer
``query`` which handles retrieval for you.
输入模式
{'type': 'object', 'title': 'list_pagesArguments', 'properties': {}}
输出模式
{'type': 'object', 'title': 'list_pagesOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': {'type': 'string'}}, 'title': 'Result'}}}
list_proposed_actions
List the key's workspace's proposed actions (the approval queue).
Read-only. Optionally filter by ``status`` (proposed / approved /
executing / done / failed / dismissed). Returns ``{id, action_type,
status, source, title, source_doc_id, external_id}`` per proposal.
NOTE: MCP can read and PROPOSE actions but deliberately cannot approve
or execute them â a human approves every action in the app UI.
输入模式
{'type': 'object', 'title': 'list_proposed_actionsArguments', 'properties': {'status': {'type': 'string', 'title': 'Status', 'default': ''}}}
输出模式
{'type': 'object', 'title': 'list_proposed_actionsOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'title': 'Result'}}}
list_repos
List the repos ingested into the key's workspace.
Returns ``{full_name, branch, last_ingested_at}`` records. Use this when
the agent needs to know what context is available before asking a
question.
Reads what ingest actually recorded for this namespace: ``repos.json``
(the repoâclone map every other read path resolves through) plus the
per-repo ``_state`` files that carry the branch and the last run's
timestamp.
It used to read a Firestore subcollection ``users/{uid}/repos``, which
was wrong twice over. It was keyed by the person rather than the
workspace â the bug this module was fixed for â and nothing in the
codebase has ever written to that path, so the tool returned an empty
list to everyone, forever. Hence ``branch`` rather than the old
``default_branch``: the state file records the branch that was actually
ingested, and no caller can be depending on a key that never had a row
under it.
输入模式
{'type': 'object', 'title': 'list_reposArguments', 'properties': {}}
输出模式
{'type': 'object', 'title': 'list_reposOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'title': 'Result'}}}
list_skills
List the compiled skills (recurring procedures) in the key's workspace.
Skills are agent-executable SKILL.md pages mined from that workspace's
wiki by the skills compiler. Returns ``{name, title, description,
confidence, last_compiled, sources}`` records â feed a ``name`` to
``get_skill`` for the full markdown. Empty list = nothing compiled
yet (the user can run a compile from Enhanciar's UI or API).
输入模式
{'type': 'object', 'title': 'list_skillsArguments', 'properties': {}}
输出模式
{'type': 'object', 'title': 'list_skillsOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'title': 'Result'}}}
propose_action
Propose a new action for human approval (does NOT execute it).
``action_type`` is a registered executor id (e.g. ``jira.create_issue``,
``linear.create_issue``, ``github.create_issue``). The proposal lands in
the key's workspace's approval queue where a person picks the target and
approves it â approve/execute are intentionally NOT exposed over MCP.
Returns the created ``{id, action_type, status}`` or an ``error``.
输入模式
{'type': 'object', 'title': 'propose_actionArguments', 'required': ['action_type', 'title'], 'properties': {'title': {'type': 'string', 'title': 'Title'}, 'evidence': {'type': 'string', 'title': 'Evidence', 'default': ''}, 'action_type': {'type': 'string', 'title': 'Action Type'}, 'description': {'type': 'string', 'title': 'Description', 'default': ''}}}
输出模式
{'type': 'object', 'title': 'propose_actionDictOutput', 'additionalProperties': True}
query
Ask Enhanciar a natural-language question grounded in the key's workspace.
This is the high-level tool â use it for any "what does X do",
"why did we choose Y", "where is Z handled" question. It runs
the full retrieval + synthesis pipeline and returns the answer
plus citations.
Args:
question: Natural-language question.
model: Optional model id override (``gemini-2.5-flash``,
``gpt-4o``, ``claude-sonnet-4-5``, etc.). If omitted the
saved default is used â the workspace's in a team workspace,
the caller's own in a personal one.
Returns ``{answer, sources, model}`` â ``sources`` is a list of
``{category, name, url}`` citations the LLM grounded its answer
in. Surface them to the human so they can verify. When the workspace
has nothing ingested at all you get ``{answer, empty_brain: true}``
and no sources: that is a statement about the workspace, not a failed
search, so rephrasing the question will not change it.
输入模式
{'type': 'object', 'title': 'queryArguments', 'required': ['question'], 'properties': {'model': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Model', 'default': None}, 'question': {'type': 'string', 'title': 'Question'}}}
输出模式
{'type': 'object', 'title': 'queryDictOutput', 'additionalProperties': True}
search_wiki
Substring search across the wiki pages in the key's workspace.
Cheap and deterministic â no embedding required. Returns up to
``limit`` (default 20, max 50) ``{category, name, title, snippet}``
hits. The ``snippet`` is a short window around the first match,
safe to surface in chat as a citation preview.
For semantic / natural-language questions prefer ``query``.
输入模式
{'type': 'object', 'title': 'search_wikiArguments', 'required': ['query'], 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 20}, 'query': {'type': 'string', 'title': 'Query'}}}
输出模式
{'type': 'object', 'title': 'search_wikiOutput', 'required': ['result'], 'properties': {'result': {'type': 'array', 'items': {'type': 'object', 'additionalProperties': True}, 'title': 'Result'}}}
历史
近期工具变更
已更改
get_page
2026年10月1日 02:43
已添加
propose_action
2026年9月21日 02:40
已添加
list_proposed_actions
2026年9月21日 02:40
已添加
get_process_map
2026年9月21日 02:40
已添加
get_skill
2026年9月21日 02:40
已添加
list_skills
2026年9月21日 02:40
已添加
list_repos
2026年9月21日 02:40
已添加
get_graph
2026年9月21日 02:40
已添加
impact
2026年9月21日 02:40
已添加
query
2026年9月21日 02:40
已添加
get_page
2026年9月21日 02:40
已添加
search_wiki
2026年9月21日 02:40
已添加
list_pages
2026年9月21日 02:40
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