HumanMirror Forge
Five deterministic micro-tools for AI-agent data pipelines: clean, dedupe, normalize, score, detect.
Sollte ich dies verwenden
Qualität und Sicherheit
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.
Installieren
Installation mit einem Klick
Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:
{
"mcpServers": {
"forge": {
"url": "https://humanmirror.fr/api/forge/mcp/"
}
}
}Remote-Endpunkte
https://humanmirror.fr/api/forge/mcp/streamable-httpWas es kann
Tool-Inventar
Tools (5)
🔴clean_json(input, options)
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.
Eingabe-Schema
{
"type": "object",
"properties": {
"input": {
"description": "Any JSON value to normalize."
},
"options": {
"type": "object",
"properties": {
"trim_strings": {
"type": "boolean"
},
"remove_empty": {
"type": "boolean"
},
"normalize_keys": {
"type": "boolean"
},
"sort_keys": {
"type": "boolean"
}
},
"additionalProperties": false
}
},
"required": [
"input"
],
"additionalProperties": false
}🔴dedupe_records(input, options)
Remove duplicate JSON records using exact canonical matching or selected key fields. One successful call consumes 1 HumanMirror Forge credit.
Eingabe-Schema
{
"type": "object",
"properties": {
"input": {
"type": "array",
"items": {
"type": "object"
},
"description": "Array of JSON records."
},
"options": {
"type": "object",
"properties": {
"fields": {
"type": "array",
"items": {
"type": "string"
}
}
},
"additionalProperties": false
}
},
"required": [
"input"
],
"additionalProperties": false
}⚪normalize_entity(input)
Normalize entity names, domains, URLs and emails into stable machine-readable canonical values. One successful call consumes 1 HumanMirror Forge credit.
Eingabe-Schema
{
"type": "object",
"properties": {
"input": {
"description": "Entity name string or object with fields such as name, domain, url and email."
}
},
"required": [
"input"
],
"additionalProperties": false
}⚪score_data_quality(input)
Score record-array data quality using completeness, duplicate rate and field type consistency. One successful call consumes 1 HumanMirror Forge credit.
Eingabe-Schema
{
"type": "object",
"properties": {
"input": {
"type": "array",
"items": {
"type": "object"
},
"description": "Non-empty array of JSON records."
}
},
"required": [
"input"
],
"additionalProperties": false
}⚪detect_anomaly(input)
Detect numeric outliers using IQR and robust summary statistics, returning machine-readable anomaly positions. One successful call consumes 1 HumanMirror Forge credit.
Eingabe-Schema
{
"type": "object",
"properties": {
"input": {
"type": "array",
"items": {
"type": "number"
},
"description": "Numeric series."
}
},
"required": [
"input"
],
"additionalProperties": false
}Community
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