MCP-Typescribe - an MCP Server providing LLMs API information

Name: MCP-Typescribe - an MCP Server providing LLMs API information
Author: yWorks

@yWorks

代码仓库

关于 MCP-Typescribe - an MCP Server providing LLMs API information

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

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

基本信息

分类

开发工具

许可证

MIT

运行时

node

传输方式

stdio

发布者

yWorks

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

FAQ from MCP-Typescribe

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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