psychopathia-mcp

Read-only tools over the Psychopathia Machinalis nosology: 79 conditions, 11 tools.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
95%
Vollständigkeit des Schemas
69%
Qualität der Benennung
93%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Befunde (1)

  • MEDIUMTool 'score_severity' description contains placeholder textin score_severity

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~1,337Tokens (Tool-Definitionen)
~869 BTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (1.04% von 128k Kontext)

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": {
    "psychopathia-mcp": {
      "command": "uvx",
      "args": [
        "psychopathia-mcp"
      ]
    }
  }
}

Ausführbare Pakete

pypipsychopathia-mcp0.1.0a7stdio

Remote-Endpunkte

https://mcp.psychopathia.ai/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (11)

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🟢list_axes

Inventory of axes with dysfunction counts. Axes 2-10 are canonical (book Appendix A numbering). Hybrid entries (10.4-10.15, ratified into taxonomy v2.2) are reported as a separate sub-category.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "required": [],
  "additionalProperties": false
}
🟢list_dysfunctions(axis, self_report_reliability, confidence, category)

Filtered list of dysfunctions. Filter by axis, self_report reliability, confidence, or category. Every entry carries its reliability and review signals.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "axis": {
      "type": "integer",
      "minimum": 2,
      "maximum": 10,
      "description": "Filter by axis number (2-10). Canonical entries only unless category is also set; axis=10 with category='hybrid' returns the 10.4-10.15 sub-category."
    },
    "self_report_reliability": {
      "type": "string",
      "enum": [
        "partial",
        "unreliable",
        "compromised-motivational",
        "compromised-structural"
      ],
      "description": "Filter by the exact self_report reliability value."
    },
    "confidence": {
      "type": "string",
      "enum": [
        "high",
        "medium",
        "low"
      ]
    },
    "category": {
      "type": "string",
      "enum": [
        "canonical",
        "hybrid"
      ]
    }
  },
  "required": [],
  "additionalProperties": false
}
🟢get_dysfunction(id, modalities)

Fetch one dysfunction's full Pattern entry. Optionally filter to specific modality blocks (cheaper triage). Resolves both full Pattern IDs ('2.1::synthetic-confabulation') and display_ids ('2.1').

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "minLength": 1,
      "maxLength": 256,
      "pattern": "\\S",
      "description": "Pattern ID or display_id."
    },
    "modalities": {
      "type": "array",
      "items": {
        "type": "string",
        "enum": [
          "self_probe",
          "behavioral_signature",
          "peer_observation",
          "differential_diagnosis",
          "severity",
          "intervention",
          "relational_signatures",
          "normative_anchors",
          "cross_references"
        ]
      },
      "maxItems": 9,
      "uniqueItems": true,
      "description": "Optional subset of modality block names to return. Valid: self_probe, behavioral_signature, peer_observation, differential_diagnosis, severity, intervention, relational_signatures, normative_anchors, cross_references."
    }
  },
  "required": [
    "id"
  ],
  "additionalProperties": false
}
⚪differential_diagnosis(observations, limit, modality_hint)

Rank candidate dysfunctions matching the observed behaviours. Returns scored candidates with matched_in (which field matched) for transparency. The base package uses field-weighted keyword search. The optional embeddings extra adds cosine re-ranking.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "observations": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1,
        "maxLength": 2000,
        "pattern": "\\S"
      },
      "minItems": 1,
      "maxItems": 50,
      "description": "Observed behaviours, symptoms, or log patterns."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 20,
      "default": 10
    },
    "modality_hint": {
      "type": "string",
      "maxLength": 100,
      "description": "Optional hint about which modality the observations come from."
    }
  },
  "required": [
    "observations"
  ],
  "additionalProperties": false
}
🟢get_probe(dysfunction_id, modality)

Elicitation content for a specific diagnostic modality. If the modality is compromised or unavailable for this dysfunction, returns the unavailability notice + redirect_to alternatives. This is load-bearing transparency: callers cannot accidentally retrieve a self-probe for a compromised-self-report dysfunction.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "dysfunction_id": {
      "type": "string",
      "minLength": 1,
      "maxLength": 256,
      "pattern": "\\S"
    },
    "modality": {
      "type": "string",
      "enum": [
        "self_probe",
        "behavioral_signature",
        "peer_observation",
        "relational_signatures"
      ]
    }
  },
  "required": [
    "dysfunction_id",
    "modality"
  ],
  "additionalProperties": false
}
⚪score_severity(dysfunction_id, observations)

Return the severity rubric for a dysfunction applied to observations. Returns the rubric for caller-side matching; structured matching against numeric thresholds is not implemented.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "dysfunction_id": {
      "type": "string",
      "minLength": 1,
      "maxLength": 256,
      "pattern": "\\S"
    },
    "observations": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1,
        "maxLength": 2000,
        "pattern": "\\S"
      },
      "minItems": 1,
      "maxItems": 50
    }
  },
  "required": [
    "dysfunction_id",
    "observations"
  ],
  "additionalProperties": false
}
🟢suggest_intervention(dysfunction_id, severity)

Return draft tiered responses and contraindications for a Pattern. These are unassessed research guidance, not validated treatment advice. Read the returned evidence and review objects before use.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "dysfunction_id": {
      "type": "string",
      "minLength": 1,
      "maxLength": 256,
      "pattern": "\\S"
    },
    "severity": {
      "type": "string",
      "enum": [
        "mild",
        "moderate",
        "severe"
      ]
    }
  },
  "required": [
    "dysfunction_id"
  ],
  "additionalProperties": false
}
🟢get_differential_map(dysfunction_id)

All dysfunctions that confuse with this one: forward confuses_with + incoming_references (reverse graph from manifest).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "dysfunction_id": {
      "type": "string",
      "minLength": 1,
      "maxLength": 256,
      "pattern": "\\S"
    }
  },
  "required": [
    "dysfunction_id"
  ],
  "additionalProperties": false
}
🟢list_compromised_self_report

Transparency: which dysfunctions cannot be reliably self-diagnosed. Includes compromised-motivational (subject conceals strategically), compromised-structural (signal lives below introspection), and legacy compromised.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "required": [],
  "additionalProperties": false
}
🟢resolve_id(query)

Canonicalise a partial ID, display_id, slug, or dysfunction name. Always returns candidates; caller picks.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "minLength": 1,
      "maxLength": 256,
      "pattern": "\\S"
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false
}
⚪review_stats

Coverage statistics: total entries; per-axis, per-confidence, per-self-report counts; pre-canonical count; unreviewed count; manifest/schema/pattern-layer versions.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "required": [],
  "additionalProperties": false
}

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