MCP-Typescribe - an MCP Server providing LLMs API information

@yWorks

リポジトリ

基本情報

カテゴリ

開発者ツール

ライセンス

MIT

トランスポート

stdio

作者

yWorks

MCP-Typescribe - an MCP Server providing LLMs API information について

An MCP server implementation enabling LLMs to work with new APIs and frameworks

#api #typescript#typedoc#llm #mcp-server

MCP-Typescribe - an MCP Server providing LLMs API information の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-typescribe": {
      "command": "npx",
      "args": [
        "typedoc",
        "--json",
        "docs/api.json",
        "--entryPointStrategy",
        "expand",
        "path/to/your/typescript/files"
      ]
    }
  }
}

MCP-Typescribe - an MCP Server providing LLMs API information のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is MCP-Typescribe?

MCP-Typescribe is an open-source MCP server that provides large language models (LLMs) with real-time access to TypeScript API documentation. It loads TypeDoc-generated JSON and exposes query endpoints so AI coding assistants can search for symbols, get detailed information, and understand relationships within unfamiliar TypeScript APIs.

How to use MCP-Typescribe?

You generate TypeDoc JSON for your TypeScript API, build the project with npm run build, then run the server using npx mcp-typescribe@latest run-server <path-to-api.json>. AI agents such as Cline in VS Code connect to the server by specifying it in their MCP settings (e.g., cline_mcp_settings.json). The server exposes tools like search_symbols and get_symbol_details for agents to query.

Key features of MCP-Typescribe

Loads and indexes TypeDoc JSON documentation
Search symbols by name with optional kind filtering
Get detailed information about any symbol
List methods and properties of classes or interfaces
Find implementations of interfaces or subclasses
Show inheritance relationships between types

Use cases of MCP-Typescribe

Enable LLM-based coding assistants to use new or proprietary TypeScript SDKs
Let AI agents explore and understand unfamiliar APIs without retraining
Query internal API documentation dynamically rather than putting all docs into context
Help developers onboard faster by letting LLMs discover API symbols and usage patterns

よくある質問

What does MCP-Typescribe do that alternatives do not?

It converts TypeDoc JSON into a machine-readable format served via MCP, so LLMs can query specific API details on demand instead of relying on static training data or full documentation files.

What are the runtime requirements?

Node.js and npm. The server runs locally and connects to AI agents via the Model Context Protocol.

Where does the documentation data live?

You provide a local TypeDoc-generated JSON file (e.g., `docs/api.json`). The server loads and indexes this file at startup.

What transports and authentication does it use?

The README only describes a local stdio-based MCP configuration; no network transports or authentication methods are mentioned.

Is this project still actively developed?

Public development is currently suspended because no active community formed. The team is working on a separate, follow-up project for the yFiles API.

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