MCP.so
登录

WisdomForge

@hadv

关于 WisdomForge

A powerful knowledge management system that forges wisdom from experiences, insights, and best practices. Built with Qdrant vector database for efficient knowledge storage and retrieval.

基本信息

分类

数据库

许可证

MIT

运行时

node

传输方式

stdio

发布者

hadv

配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块,请前往代码仓库查看安装说明。

代码仓库

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 WisdomForge?

WisdomForge is a knowledge management system that stores and retrieves experiences, insights, best practices, and lessons learned using a vector database. It integrates with the Model Context Protocol (MCP) for use in AI IDEs like Cursor and Claude Desktop, and works with Qdrant or Chroma for efficient embedding-based retrieval.

How to use WisdomForge?

  1. Clone the repository, install dependencies, and build the project with npm install && npm run build.
  2. Create a .env file from the template and configure required environment variables: DATABASE_TYPE (qdrant/chroma), COLLECTION_NAME, and the corresponding database URL/key. Optionally set HTTP_SERVER=true for HTTP mode.
  3. Integrate with Cursor AI by adding the provided MCP configuration to your ~/.cursor/mcp.json file, or configure Claude Desktop following the run-mcp.sh script instructions.
  4. Use the MCP tools store_knowledge and retrieve_knowledge_context to store and retrieve domain knowledge.

Key features of WisdomForge

  • Intelligent knowledge management and retrieval via vector search
  • Support for multiple knowledge types (best practices, lessons learned, insights, experiences)
  • Configurable database selection between Qdrant and Chroma
  • Uses Qdrant’s built-in FastEmbed for efficient embedding generation
  • Domain knowledge storage and retrieval for AI assistants
  • Deployable to Smithery.ai cloud platform

Use cases of WisdomForge

  • Storing and retrieving team best practices and lessons learned
  • Providing contextual domain knowledge to AI coding assistants
  • Managing institutional knowledge for onboarding and training
  • Powering knowledge retrieval in MCP‑compatible tools like Cursor and Claude

FAQ from WisdomForge

What runtime and dependencies does WisdomForge require?

It requires Node.js 20.x or later, npm 10.x or later, and either a Qdrant or Chroma vector database instance.

How do I configure which database to use?

Set the DATABASE_TYPE environment variable to qdrant or chroma, and supply the corresponding URL (and API key for Qdrant). The COLLECTION_NAME variable defines the vector collection.

Where is the knowledge data stored?

All knowledge is stored in the configured external vector database (Qdrant or Chroma). WisdomForge does not persist data locally.

What transport modes are supported?

WisdomForge supports MCP transport via shell scripts (run-wisdomforge-mcp.sh for Cursor, run-mcp.sh for Claude) and an optional HTTP server mode enabled by HTTP_SERVER=true.

How do I authenticate to a remote Qdrant instance?

If you are using Qdrant, set the QDRANT_API_KEY environment variable with your API key. No authentication is documented for Chroma in the README.

评论

数据库 分类下的更多 MCP 服务器