TokenLab Model Explorer
Generates example cURL snippets for Chat Completions and Responses endpoints.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@TokenLab Model ExplorerBrowse models for text generation tasks."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
TokenLab OpenAI Apps Model Explorer
Lightweight TokenLab Model Explorer prototype for ChatGPT/OpenAI Apps SDK. It exposes an MCP Streamable HTTP endpoint plus an interactive MCP Apps widget for:
browsing TokenLab models from
/v1/models, preserving the nativedecisioncategorycomparing pricing from
/pricing.jsongenerating contract-checked examples for Chat Completions, Responses, Anthropic Messages, Gemini
generateContent, and Jev / System One decisions
This repository is intentionally small so it can be used as a public discoverability asset and a starting point for a hosted ChatGPT app.
Live MCP endpoint: https://exposure-tokenlab-openai-apps-model.vercel.app/mcp
The maintained Vercel project deploys this repository to that hostname. The historical tokenlab-model-explorer.vercel.app deployment is not attached to this project and still serves the older contract; use the maintained endpoint for Jev decision examples.
Run locally
npm install
npm test
npm startThe server listens on http://localhost:8000.
MCP endpoint:
http://localhost:8000/mcpStandalone model directory:
http://localhost:8000/widget
Opening /widget directly loads the complete public model index, with 50 results per page. Search and category filters run across the entire loaded catalog, not just the current page. The embedded MCP App resource remains a tool-result view and displays no placeholder models before the host supplies a result. MCP discovery tools still return a bounded result set for conversation use.
For ChatGPT local testing, expose the MCP endpoint with a tunnel such as ngrok, then add the /mcp URL as a connector in ChatGPT developer mode.
The Express app is also exported as the default module, so Vercel can deploy this repository without a custom adapter.
Related MCP server: APIAny MCP
Environment
TOKENLAB_API_BASE=https://api.tokenlab.sh
PORT=8000Tools
Tool | Purpose |
| Browse TokenLab models by category or search query. |
| Compare pricing metadata for up to 8 model IDs. |
| Generate cURL snippets for OpenAI-compatible and native TokenLab endpoints. |
Discovery inputs
https://api.tokenlab.sh/v1/modelsand/v1/models/{id}https://api.tokenlab.sh/pricing.jsonhttps://api.tokenlab.sh/integrations.jsonhttps://docs.tokenlab.sh/openapi.json
Notes
The standalone
/widgetand Hugging Face static Space sharehuggingface/index.html. Upload that exact file to the existingkiln4758/tokenlab-model-explorerSpace after validation; do not independently edit its pagination or endpoint logic in two places./widgetreads the catalog through same-origin/public/v1/models,/public/v1/models/:model, and/public/pricing.json. These read-only routes forward neither credentials nor arbitrary URLs; the static Space retains direct public API reads from its allowed origin.This app does not require a TokenLab API key for discovery tools.
Inference tools should use
@tokenlabai/mcp-server; this repo focuses on model exploration and endpoint examples. System One examples are synchronous typed decisions, not chat replies or authorization to execute actions.The widget follows the MCP Apps pattern: tools are registered with UI metadata, and the HTML resource is served as an MCP app resource.
This server cannot be deployed
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