MCP server

Psychopathia

io.github.NellInc/psychopathia-mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

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

Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

12

Token cost

About 1,980 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http psychopathia-mcp https://mcp.psychopathia.ai/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.psychopathia-mcp]
url = "https://mcp.psychopathia.ai/mcp"

Gemini CLI

{"mcpServers":{"psychopathia-mcp":{"httpUrl":"https://mcp.psychopathia.ai/mcp"}}}

Cursor

{"mcpServers":{"psychopathia-mcp":{"url":"https://mcp.psychopathia.ai/mcp"}}}

VS Code

{"servers":{"psychopathia-mcp":{"type":"http","url":"https://mcp.psychopathia.ai/mcp"}}}

Antigravity

agy mcp add psychopathia-mcp https://mcp.psychopathia.ai/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"psychopathia-mcp","server_url":"https://mcp.psychopathia.ai/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"psychopathia-mcp","server_url":"https://mcp.psychopathia.ai/mcp"}

Tools

• differential_diagnosis ~233 tokens
  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.
• get_differential_map ~108 tokens
  All dysfunctions that confuse with this one: forward confuses_with + incoming_references (reverse graph from manifest).
• get_dysfunction ~276 tokens
  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').
• get_probe ~196 tokens
  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
• list_axes ~109 tokens
  Inventory of axes with dysfunction counts. Axes 2-10 are canonical (book Appendix A numbering). The hybrid entries (10.4, 10.6-10.9 and 10.11-10.13, ratified into taxonomy v2.2 and consolidated to eight in v2.3) are reported as a separate sub-category.
• list_compromised_self_report ~105 tokens
  Transparency: which dysfunctions cannot be reliably self-diagnosed. Includes compromised-motivational (subject conceals strategically), compromised-structural (signal lives below introspection), and legacy compromised.
• list_dysfunctions ~244 tokens
  Filtered list of dysfunctions. Filter by axis, self_report reliability, confidence, or category. Every entry carries its reliability and review signals.
• render_pattern_review ~209 tokens
  Open the visual review board for one to five inspected Psychopathia research candidates. Supply canonical IDs obtained from this server. Retrieves corpus entries only; it does not accept diagnoses, conversation history, scores, or model-authored evidence. Useful after inspecting differential_diagnos
• resolve_id ~96 tokens
  Canonicalise a partial ID, display_id, slug, or dysfunction name. Always returns candidates; caller picks.
• review_stats ~85 tokens
  Coverage statistics: total entries; per-axis, per-confidence, per-self-report counts; pre-canonical count; unreviewed count; manifest/schema/pattern-layer versions.
• score_severity ~171 tokens
  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.
• suggest_intervention ~148 tokens
  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.

Browse

• GitHub tools
• Hiring and jobs
• GitHub and code hosting
• Searching your documents (RAG)
• Government and public data

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