repocks
Allows indexing of Obsidian vaults (Markdown notes) to make them searchable and queryable through the MCP server for AI-powered Q&A.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@repocksSummarize my meeting notes from Q3"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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-largeBasic Usage
Index your documents:
repocks indexThis scans your Markdown files and creates a searchable index.
Start the MCP server:
repocks startNow 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:
Open Claude Desktop settings
Go to Developer > Model Context Protocol
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.jsonpathsEnsure
.mdfiles exist in those locationsRun
repocks indexto rebuild the index
"Cannot connect to Ollama"
Start Ollama:
ollama serveCheck if models are installed:
ollama listVerify 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
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