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Welcome to OpenGround

OpenGround lets you give controlled access to documentation to AI agents. Everything happens on-device.
OpenGround is an on-device RAG system that extracts documentation from git repos and sitemaps, embeds it for semantic search, and exposes it to AI agents via MCP.

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What is OpenGround?

OpenGround bridges the gap between your AI coding assistant and official documentation. Instead of relying on potentially outdated training data, your AI agents can search accurate, up-to-date documentation stored locally on your machine.

On-Device Processing

All data stays on your machine. No cloud services, no API keys, complete privacy.

Hybrid Search

Combines semantic vector search with BM25 full-text search for accurate results.

MCP Integration

Seamlessly integrates with Claude Code, Cursor, OpenCode, and other MCP-compatible agents.

Multi-Version Support

Store and query multiple versions of the same library simultaneously.

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Architecture

      ┌─────────────────────────────────────────────────────────────────────┐
      │                           OPENGROUND                                │
      ├─────────────────────────────────────────────────────────────────────┤
      │                                                                     │
      │       SOURCE                  PROCESS              STORAGE/CLIENT   │
      │                                                                     │
      │    ┌──────────┐      ┌───────────┐   ┌──────────┐   ┌──────────┐    │
      │    │ git repo ├─────>│  Extract  ├──>│  Chunk   ├──>│ LanceDB  │    │
      │    |   -or-   |      │ (raw_data)│   │   Text   │   │ (vector  │    │
      │    │ sitemap  │      └───────────┘   └──────────┘   │  +BM25)  │    │
      │    │   -or-   │                           │         └────┬─────┘    │
      │    │ local dir│                           │              │          │
      │    └──────────┘                           │              │          │
      │                                           ▼              │          │
      │                                    ┌───────────┐         │          │
      │                                    │   Local   |<────────┘          │
      │                                    │ Embedding │         │          │
      │                                    │   Model   │         ▼          │
      │                                    └───────────┘  ┌─────────────┐   │
      │                                                   │ CLI / MCP   │   │
      │                                                   │  (hybrid    │   │
      |                                                   |   search)   |   |
      │                                                   └─────────────┘   │
      │                                                                     │
      └─────────────────────────────────────────────────────────────────────┘
OpenGround follows a simple pipeline:
  1. Source - Extract docs from git repos, sitemaps, or local directories
  2. Process - Chunk text and generate embeddings using local models
  3. Storage - Store in LanceDB with vector + BM25 indices
  4. Query - Search via CLI or expose to AI agents through MCP

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Key Features

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Privacy First

All processing happens on your machine. No data leaves your device. No cloud dependencies.

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Flexible Sources

Extract documentation from:
  • Git repositories - Clone specific versions, sparse checkout for docs folders
  • Sitemaps - Crawl documentation sites automatically
  • Local directories - Index your own documentation or notes
Hybrid search combines:
  • Semantic search - Understands meaning and context
  • BM25 - Traditional keyword matching for precise queries

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AI Agent Integration

Seamless integration with:
  • Claude Code
  • Cursor
  • OpenCode
  • Any MCP-compatible agent

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Version Management

  • Store multiple versions of the same library
  • Query specific versions
  • Incremental updates with content hash detection

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Multiple Embedding Backends

  • Sentence-Transformers - Full GPU/MPS/CPU support, larger package
  • FastEmbed - Lightweight, CPU-optimized
  • FastEmbed-GPU - Experimental CUDA support

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Use Cases

Give your AI assistant access to official documentation without polluting your conversation context. Ask questions like “How do I use React’s useEffect hook?” and get answers directly from the React documentation.
Work with multiple versions of the same framework? Store React 17 and React 18 docs side-by-side, query the version you’re currently using.
Download documentation once, use it forever offline. Perfect for planes, remote locations, or when you want to avoid distractions.
Index your company’s internal documentation and make it searchable for AI agents, without sending it to the cloud.

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Supported File Formats

When extracting from git repos or local directories, OpenGround supports:
  • Markdown (.md, .mdx)
  • reStructuredText (.rst)
  • Plain text (.txt)
  • Jupyter Notebooks (.ipynb)
  • HTML (.html, .htm)

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How It Works

OpenGround uses a Retrieval-Augmented Generation (RAG) approach:
  1. Extract - Download documentation from various sources
  2. Chunk - Split documents into manageable pieces (800 chars with 200 char overlap)
  3. Embed - Generate vector embeddings using BGE-small-en-v1.5 model
  4. Index - Store in LanceDB with both vector and BM25 full-text indices
  5. Query - Search using hybrid approach that combines semantic and keyword matching
  6. Serve - Expose results via CLI or MCP server for AI agents

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Next Steps

Quickstart

Get up and running in 5 minutes

Installation

Detailed installation instructions

Add Documentation

Learn how to add your first library

MCP Integration

Connect to your AI coding assistant