MCP Servers

pangram-mcp

Exposes an analyze tool to classify text as human-written, AI-generated, or AI-assisted using Pangram Labs API.

README

pangram-mcp

An MCP server for Pangram Labs AI-generated-text detection. Exposes a single analyze tool that classifies text as human-written, AI-generated, or AI-assisted — with an overall verdict, per-class fractions, and a per-segment breakdown.

The API key stays in the server's environment and is sent as the x-api-key header; it is never returned to the model or logged. Callers pass text and receive a classification — they never handle the credential.

Install / run

Requires an API key from Pangram Labs:

export PANGRAM_API_KEY="your-key"
uvx pangram-mcp

MCP client config

{
  "mcpServers": {
    "pangram": {
      "command": "uvx",
      "args": ["pangram-mcp"],
      "env": { "PANGRAM_API_KEY": "your-key" }
    }
  }
}

Configuration

Env var	Required	Default	Purpose
`PANGRAM_API_KEY`	yes	—	Pangram Labs API key.
`PANGRAM_API_BASE`	no	`https://text.api.pangram.com/v3`	Endpoint override.
`PANGRAM_TIMEOUT`	no	`60`	Request timeout (seconds).

Tool: `analyze`

Detect AI-generated text.

Parameter	Type	Description
`text`	string	Text to classify (required).
`public_dashboard_link`	bool	Request a public shareable Pangram dashboard link (default `false`; only for non-sensitive text).

The tool takes inline text only — not a file path. Reading files server-side would let a caller exfiltrate any file the process can read, bypassing the harness's permission-gated file tools. Read files with your own tools and pass the text.

Returns structured output: prediction, prediction_short, headline, fraction_ai / fraction_ai_assisted / fraction_human (0.0–1.0), num_ai_segments / num_ai_assisted_segments / num_human_segments, a windows array (per-segment label, ai_assistance_score, confidence, indices), and an optional dashboard_link.

Development

uv sync --extra dev
uv run pytest
uv run ruff check .
uv run mypy src

License

MIT — see LICENSE.

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