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Serveur MCP

HumanMirror Forge

fr.humanmirror/forge
Données et analytique Outils développeur Public et accessible MCP 2026-07-28

Ce que fait ce MCP

Cleans, deduplicates, canonicalizes, scores, and analyzes JSON records for data quality and numeric anomalies.

Capacités

Outils

5 outils
clean_json
Normalize JSON deterministically: trim strings, normalize object keys, optionally remove empty values, and sort keys for stable downstream processing. One successful call consumes 1 HumanMirror Forge credit.
Schéma d’entrée 
{'type': 'object', 'required': ['input'], 'properties': {'input': {'description': 'Any JSON value to normalize.'}, 'options': {'type': 'object', 'properties': {'sort_keys': {'type': 'boolean'}, 'remove_empty': {'type': 'boolean'}, 'trim_strings': {'type': 'boolean'}, 'normalize_keys': {'type': 'boolean'}}, 'additionalProperties': False}}, 'additionalProperties': False}
dedupe_records
Remove duplicate JSON records using exact canonical matching or selected key fields. One successful call consumes 1 HumanMirror Forge credit.
Schéma d’entrée 
{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'array', 'items': {'type': 'object'}, 'description': 'Array of JSON records.'}, 'options': {'type': 'object', 'properties': {'fields': {'type': 'array', 'items': {'type': 'string'}}}, 'additionalProperties': False}}, 'additionalProperties': False}
detect_anomaly
Detect numeric outliers using IQR and robust summary statistics, returning machine-readable anomaly positions. One successful call consumes 1 HumanMirror Forge credit.
Schéma d’entrée 
{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'array', 'items': {'type': 'number'}, 'description': 'Numeric series.'}}, 'additionalProperties': False}
normalize_entity
Normalize entity names, domains, URLs and emails into stable machine-readable canonical values. One successful call consumes 1 HumanMirror Forge credit.
Schéma d’entrée 
{'type': 'object', 'required': ['input'], 'properties': {'input': {'description': 'Entity name string or object with fields such as name, domain, url and email.'}}, 'additionalProperties': False}
score_data_quality
Score record-array data quality using completeness, duplicate rate and field type consistency. One successful call consumes 1 HumanMirror Forge credit.
Schéma d’entrée 
{'type': 'object', 'required': ['input'], 'properties': {'input': {'type': 'array', 'items': {'type': 'object'}, 'description': 'Non-empty array of JSON records.'}}, 'additionalProperties': False}
Historique

Modifications récentes des outils

Ajouté
detect_anomaly
17 September 2026 12:39
Ajouté
score_data_quality
17 September 2026 12:39
Ajouté
normalize_entity
17 September 2026 12:39
Ajouté
dedupe_records
17 September 2026 12:39
Ajouté
clean_json
17 September 2026 12:39
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