openground

openground

On-device documentation search for agents

Category
Visit Server

README

openground

PyPI version

tldr: 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. It uses a local embedding model, and local lancedb for storing embeddings and for hybrid vector similarity and BM25 full-text search.

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)   |   |
      │                                                   └─────────────┘   │
      │                                                                     │
      └─────────────────────────────────────────────────────────────────────┘

Quick Start

Installation

Recommended to install with uv:

uv tool install openground # Larger package size, automatic GPU/MPS/CPU support
uv tool install 'openground[fastembed]' # Lightweight CPU support
uv tool install 'openground[fastembed-gpu]' # Experimental CUDA/GPU support through fastembed

or

pip install openground

Add Documentation

Openground can source documentation from git repos, sitemaps, or local directories.

To add documentation from a git repo to openground, run:

openground add library-name \
  --source https://github.com/example/example.git \
  --docs-path docs/ \
  --version v1.0.0 \ # gets v1.0.0 docs using git tags
  -y

The --version flag specifies a git tag to checkout (defaults to latest).

To add documentation from a sitemap to openground:

openground add library-name \
  --source https://docs.example.com/sitemap.xml \
  --filter-keyword docs \ 
  --filter-keyword blog \
  -y

To add documentation from a local path to openground:

# Absolute path
openground add library-name --source /path/to/docs -y

# Home directory
openground add library-name --source ~/path/to/docs -y

# Relative path (from current directory)
openground add library-name --source ./docs -y
openground add library-name --source ../docs -y
openground add library-name --source docs -y

Git and local directory additions support .md, .rst, .txt, .mdx, .ipynb, .html, and .htm files.

This will download the docs, embed them, and store them into lancedb. All locally.

Multiple versions of the same library can be stored and queried independently.

Sources Files

Openground uses sources.json files to store library source configurations. When you add documentation with --source, openground remembers the source URL so you can add/update the same library later by just specifying its name.

How Sources Files Work

There are two types of sources files:

  1. User Sources File (~/.openground/sources.json)

    • Shared across all your projects
    • Created automatically when you first use --source flag
    • This is where new sources are saved by default
  2. Project Sources File (.openground/sources.json)

    • Project-specific overrides
    • Created automatically in each project when you add a source
    • Takes priority over user sources when both exist

Priority Order

When looking up a library by name, openground checks:

  1. Custom path via --sources-file flag
  2. Project-local .openground/sources.json (if exists)
  3. User ~/.openground/sources.json (if exists)
  4. Package-level bundled sources

Example Workflow

# In project1: Add library with source
cd project1/
openground add fastapi --source https://github.com/tiangolo/fastapi.git --docs-path docs/

# In project2: Same library is now available by name!
cd ../project2/
openground add fastapi  # Finds source from ~/.openground/sources.json

# Project-specific override: Add a different version for this project
echo '{"fastapi": {"type": "git_repo", "repo_url": "https://github.com/tiangolo/fastapi.git", "docs_paths": ["docs"], "languages": ["python"]}}' > .openground/sources.json

Managing Sources

Sources are stored as JSON with this structure:

{
  "fastapi": {
    "type": "git_repo",
    "repo_url": "https://github.com/tiangolo/fastapi",
    "docs_paths": ["docs"],
  },
  "numpy": {
    "type": "sitemap",
    "sitemap_url": "https://numpy.org/doc/sitemap.xml",
    "filter_keywords": ["docs/"]
  }
}

To disable automatic source saving:

openground config set sources.auto_add_local false

Use with AI Agents

To install the MCP server:

# For Cursor
openground install-mcp --cursor

# For Claude Code
openground install-mcp --claude-code

# For OpenCode
openground install-mcp --opencode

# For any other agent
openground install-mcp

Now your AI assistant can search your stored documentation automatically!

Example Workflow

Here's how to add the fastembed documentation and make it available to Claude Code:

# 1. Install openground
uv tool install openground

# 2. Add fastembed to openground
openground add fastembed --source https://github.com/qdrant/fastembed.git --docs-path docs/ --version v0.7.4 -y

# 3. Configure Claude Code to use openground MCP
openground install-mcp --claude-code

# 4. Restart Claude Code
# Now you can ask: "What models are available in fastembed?"
# Claude will search the fastembed docs automatically!

Claude Code Agent

Openground includes a custom Claude Code agent that searches official documentation without polluting your main conversation context. See docs/claude-code-agent.md for installation and usage instructions.

MCP Usage Statistics

To see how many times each tool in the MCP server has been called:

openground stats show # show stats
openground stats clear # reset stats

Development

To contribute or work on openground locally:

git clone https://github.com/poweroutlet2/openground.git
cd openground
uv sync .

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured