TokenLab MCP Server

MCP server for TokenLab model discovery, pricing, native endpoint guidance, and optional inference helpers.

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TokenLab MCP Server

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Model Context Protocol server for TokenLab public model discovery, pricing, OpenAI-compatible Chat Completions, and native Responses, Anthropic Messages, and Gemini inference.

It exposes public catalog tools for agents that need to choose models, inspect supported request formats, or compare pricing before calling TokenLab APIs. Optional inference tools require TOKENLAB_API_KEY.

Tools

  • list_models - List public TokenLab models, optionally filtered by recommended_for.
  • get_model - Fetch public model details for one model ID.
  • get_model_pricing - Fetch pricing details for one model ID.
  • compare_models - Compare details and pricing for several model IDs.
  • get_api_overview - Fetch the agent-readable llms.txt overview.
  • create_chat_completion - Call TokenLab's OpenAI-compatible non-streaming Chat Completions API. Requires TOKENLAB_API_KEY.
  • create_response - Call TokenLab Responses API. Requires TOKENLAB_API_KEY.
  • create_anthropic_message - Call TokenLab Anthropic Messages API. Requires TOKENLAB_API_KEY.
  • create_gemini_content - Call TokenLab Gemini generateContent API. Requires TOKENLAB_API_KEY.

Run

npm install
npm start

Install from npm:

npx -y @tokenlabai/mcp-server

Agent-assisted installers can follow llms-install.md for a minimal, credential-safe setup and verification flow.

Run in Docker:

docker build -t tokenlab-mcp-server .
docker run --rm -i tokenlab-mcp-server

Add -e TOKENLAB_API_KEY when using inference tools. Public catalog tools do not require a key.

Claude Desktop style config:

{
  "mcpServers": {
    "tokenlab-model-catalog": {
      "command": "npx",
      "args": ["-y", "@tokenlabai/mcp-server"],
      "env": {
        "TOKENLAB_API_BASE": "https://api.tokenlab.sh"
      }
    }
  }
}

No TokenLab API key is required for the public catalog tools. Set TOKENLAB_API_KEY only when you want the inference tools to call paid TokenLab APIs. create_chat_completion supports OpenAI-compatible messages, multimodal content parts, function calling, and common generation controls. The native tools preserve structured Responses input, Anthropic message blocks and tools, and Gemini contents, multimodal parts, tools, and generation config. The prompt shortcuts remain available for simple Anthropic and Gemini calls. MCP tools return a normal JSON result, so streaming is intentionally disabled.

Environment

  • TOKENLAB_API_BASE: optional, defaults to https://api.tokenlab.sh
  • TOKENLAB_API_KEY: optional; required only for create_chat_completion, create_response, create_anthropic_message, and create_gemini_content
  • TOKENLAB_REQUEST_TIMEOUT_MS: optional request timeout in milliseconds, defaults to 30000

MCP Registry Metadata

This repository includes server.json for the official MCP Registry.

Current publication:

  • npm package: @tokenlabai/mcp-server@0.3.0
  • MCP registry name: io.github.hedging8563/tokenlab
  • Official MCP Registry status: active
  • package.json.mcpName: io.github.hedging8563/tokenlab

For a new release:

  1. Bump the matching versions in package.json, package-lock.json, and server.json.
  2. Push a matching tag such as v0.3.0.
  3. The publish workflow tests and publishes npm through trusted publishing, then publishes the MCP Registry entry through GitHub Actions OIDC.

The same workflow can be run manually from main to republish only the current MCP Registry metadata. No npm or MCP Registry token is stored in GitHub.

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