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repocks

v1.2.1

Published

Transform your Markdown documentation into an intelligent knowledge base. Repocks indexes your documents and provides AI-powered search and Q&A capabilities through an MCP server.

Downloads

6

Readme

Repocks

Transform your Markdown documentation into an intelligent knowledge base. Repocks indexes your documents and provides AI-powered search and Q&A capabilities through an MCP server.

What is Repocks?

Repocks turns your collection of Markdown files into a searchable knowledge base that AI assistants can query. Whether you have technical documentation, meeting notes, or personal knowledge management files, Repocks makes them accessible through natural language queries.

Key Benefits

  • Smart Search: Find relevant information using natural language, not just keywords
  • AI-Powered Q&A: Get comprehensive answers based on your documentation
  • Easy to Update: Run index command to sync changes in your documents
  • Works with Any MCP Client: Compatible with Claude Desktop, Cline, and other MCP-supporting AI tools
  • Local & Private: Your data stays on your machine

Quick Start

Prerequisites

  • Node.js 20.9.0 or higher
  • Ollama running locally
  • npm, yarn, pnpm, etc.

Installation

# Install Repocks
npm install -g repocks

# Download required AI models
ollama pull qwen3:4b
ollama pull mxbai-embed-large

Basic Usage

  1. Index your documents:

    repocks index

    This scans your Markdown files and creates a searchable index.

  2. Start the MCP server:

    repocks start

    Now your knowledge base is ready to answer questions!

    We recommend registering with Coding Agent (such as Claude Code, Cline, etc.) as shown in the example below.

    # Register mcp server in Claude Code
    claude mcp add repocks -- repocks start

Configuration

Specifying Document Locations

By default, Repocks indexes:

  • ~/.repocks/**/*.md (your personal notes)
  • ./docs/**/*.md (project documentation)

To customize, create repocks.config.json:

{
  "targets": [
    "./my-notes/**/*.md",
    "./team-docs/**/*.md",
    "~/Documents/obsidian/**/*.md"
  ]
}

Using Different AI Models

Set environment variables to use different Ollama models:

# Use a different LLM
export OLLAMA_LLM="llama2:13b"

# Use a different embedding model
export OLLAMA_EMBEDDING_MODEL="nomic-embed-text"

# Use a remote Ollama instance
export OLLAMA_BASE_URL="http://192.168.1.100:11434/api"

Integration with Claude Desktop

Add Repocks to your Claude Desktop configuration:

  1. Open Claude Desktop settings
  2. Go to Developer > Model Context Protocol
  3. Add the following configuration:
{
  "mcpServers": {
    "repocks": {
      "command": "repocks",
      "args": ["start"]
    }
  }
}

Now you can ask Claude questions about your documentation!

Example Use Cases

Personal Knowledge Management

  • "What did I write about project architecture last month?"
  • "Find my notes on Docker best practices"
  • "Summarize my meeting notes from Q3"

Technical Documentation

  • "How do I configure the authentication module?"
  • "What are the API endpoints for user management?"
  • "Show me examples of error handling in our codebase"

Research & Learning

  • "What have I learned about machine learning?"
  • "Find all references to distributed systems"
  • "Create a summary of my React hooks notes"

Commands Reference

repocks index

Scans and indexes all Markdown files in configured paths. Run this:

  • After adding new documents
  • When you've made significant changes
  • To ensure your index is up-to-date

repocks start

Starts the MCP server. Keep this running while using AI assistants.

Troubleshooting

"No documents found"

  • Check your repocks.config.json paths
  • Ensure .md files exist in those locations
  • Run repocks index to rebuild the index

"Cannot connect to Ollama"

  • Start Ollama: ollama serve
  • Check if models are installed: ollama list
  • Verify the API URL matches your setup

"Search returns irrelevant results"

  • Try more specific queries
  • Re-index your documents
  • Consider using a more powerful embedding model

License

MIT