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wisdomforge

by hadv·4·Score 33

Knowledge management MCP server using Qdrant vector database for storing and retrieving domain knowledge.

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Overview

WisdomForge is an MCP server that implements knowledge management capabilities using vector databases. It allows users to store and retrieve various types of knowledge including best practices, lessons learned, insights, and experiences. The server uses Qdrant's FastEmbed for efficient embedding generation and supports both Qdrant and Chroma as vector backends. It provides tools for storing domain knowledge and retrieving relevant context, making it useful for organizations looking to capture and leverage institutional knowledge.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

you:Store organizational best practices and lessons learned for team access
you:Retrieve relevant domain knowledge during AI assistant conversations
you:Capture and retrieve expert insights for decision support
you:What vector databases does WisdomForge support?
you:How do I integrate WisdomForge with Claude Desktop?

When to choose this

Choose WisdomForge when you need to integrate specialized knowledge bases into AI workflows, particularly for storing and retrieving domain-specific best practices and insights.

When NOT to choose this

Avoid if you need broader document management capabilities beyond specialized knowledge retrieval, or if you're looking for a solution with more comprehensive collaboration features.

Tools this server exposes

2 tools extracted from the README
  • store_knowledge

    Store domain-specific knowledge in a vector database

  • retrieve_knowledge_context

    Retrieve relevant domain knowledge from a vector database

Comparable tools

memgptsemantic-search-mcpvector-store-mcpnotion-mcp

Installation

Installation

  1. Clone the repository:
git clone https://github.com/hadv/wisdomforge
cd wisdomforge
  1. Install dependencies:
npm install
  1. Create a .env file based on .env.example:
cp .env.example .env
  1. Configure your environment variables in .env:
DATABASE_TYPE=qdrant
COLLECTION_NAME=wisdom_collection
QDRANT_URL=https://your-qdrant-instance.example.com
QDRANT_API_KEY=your_api_key
HTTP_SERVER=true
PORT=3000
  1. Build the project:
npm run build

Claude Desktop Configuration

Add this configuration in Claude's settings:

{
  "processes": {
    "knowledge_server": {
      "command": "/path/to/wisdomforge/run-mcp.sh",
      "args": []
    }
  },
  "tools": [
    {
      "name": "store_knowledge",
      "description": "Store domain-specific knowledge in a vector database",
      "provider": "process",
      "process": "knowledge_server"
    },
    {
      "name": "retrieve_knowledge_context",
      "description": "Retrieve relevant domain knowledge from a vector database",
      "provider": "process",
      "process": "knowledge_server"
    }
  ]
}

FAQ

What vector databases does WisdomForge support?
WisdomForge supports both Qdrant and Chroma as vector database backends. You can configure which one to use via the DATABASE_TYPE environment variable.
How do I integrate WisdomForge with Claude Desktop?
Add the process and tool configurations to Claude's settings.json file as shown in the README. Make sure the run-mcp.sh script is executable and the paths are correct.

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Last updated · Auto-generated from public README + GitHub signals.