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Knowledge MCP Server

by sven-borkert
MIT License

Knowledge MCP Server

A Model Context Protocol (MCP) server that provides centralized knowledge management for your projects. Store, search, and maintain project-specific knowledge that persists across sessions.

Features

  • Project-aware: Automatically identifies projects by git remote URL
  • Structured knowledge: Organize information in YAML-frontmatter markdown documents
  • Full-text search: Search across all project knowledge documents
  • Chapter-based organization: Structure documents with chapters for easy navigation
  • Main instructions: Replace CLAUDE.md with centralized project instructions
  • Secure: Path validation, input sanitization, and safe file operations

Installation

npx @spothlynx/knowledge-mcp

Via npm (global installation)

npm install -g @spothlynx/knowledge-mcp knowledge-mcp

Requirements

  • Node.js 14+
  • Python 3.11+
  • Git (for project identification)

Configuration

Claude Desktop

Add to your Claude Desktop configuration (claude_desktop_config.json):

{ "mcpServers": { "knowledge": { "command": "npx", "args": ["-y", "@spothlynx/knowledge-mcp"] } } }

VSCode Claude Extension

Add to your VSCode settings:

{ "claude.mcpServers": { "knowledge": { "command": "npx", "args": ["-y", "@spothlynx/knowledge-mcp"] } } }

Other MCP Clients

# Direct execution npx @spothlynx/knowledge-mcp # Or if installed globally knowledge-mcp

Usage

The Knowledge MCP Server provides the following tools:

Managing Project Instructions

  • Get project instructions: Retrieve the main project instructions (replaces CLAUDE.md)
  • Update project instructions: Create or update main project instructions

Knowledge Documents

  • Create knowledge file: Create structured documents with metadata and chapters
  • Search knowledge: Full-text search across all project documents
  • Update chapter: Modify specific chapters within documents
  • Delete knowledge file: Remove knowledge documents

Resources (Read-only)

  • knowledge://projects/{project_id}/main - Read main project instructions
  • knowledge://projects/{project_id}/files - List all knowledge files
  • knowledge://projects/{project_id}/chapters/{filename} - List chapters in a document

Storage Location

Knowledge is stored in your home directory:

~/.knowledge-mcp/ └── projects/ └── {git-remote-url}/ # Project identified by git remote ├── main.md # Main project instructions └── knowledge/ # Knowledge documents └── *.md # Individual knowledge files

Document Format

Knowledge documents use YAML frontmatter with markdown content:

--- title: API Documentation keywords: [api, rest, endpoints] --- # Introduction Overview of the API... ## Chapter: Authentication How to authenticate with the API... ## Chapter: Endpoints Available API endpoints...

Development

Setup Development Environment

# Clone the repository git clone https://github.com/sven-borkert/knowledge-mcp.git cd knowledge-mcp # Create virtual environment python3 -m venv venv source venv/bin/activate # Install in development mode with all dependencies pip install -e ".[dev]" # Run tests pytest tests/ -v # Run code quality checks python check_code_quality.py --fix

Testing with MCP Inspector

# Test with MCP Inspector npx @modelcontextprotocol/inspector python -m knowledge_mcp.server # Or if installed npx @modelcontextprotocol/inspector knowledge-mcp

Building and Distribution

# Build distribution packages python -m build # Upload to PyPI (when ready) twine upload dist/*

Security

  • Path traversal protection
  • Input sanitization for filenames
  • Safe YAML parsing (no code execution)
  • Atomic file writes
  • Secure project identification

Troubleshooting

Python not found

# Ensure Python 3.11+ is installed python3 --version # On Windows python --version

Permission errors

# Check directory permissions ls -la ~/.knowledge-mcp/ # Create directory if needed mkdir -p ~/.knowledge-mcp/projects

MCP connection issues

# Test with MCP Inspector npx @modelcontextprotocol/inspector knowledge-mcp # Check server logs knowledge-mcp 2>&1 | tee server.log

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Run tests and code quality checks
  4. Submit a pull request

License

MIT License - see LICENSE file for details

Support

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