Omni Rag
FreeNot checkedEnables token-efficient semantic search and analysis over any directory of files through hybrid search, directory overview, structural analysis, and dependency
About
Enables token-efficient semantic search and analysis over any directory of files through hybrid search, directory overview, structural analysis, and dependency graphs.
README
A general-purpose RAG MCP plugin for token-efficient semantic search over any directory of files. Auto-ingests the current working directory on first search and provides hybrid search (BM25 + semantic), directory overview, structural analysis, and dependency graphs.
Zero-config by default: local Qdrant storage, ONNX embeddings, no external services required. Supports code, markdown, PDFs, CSVs, and more via pluggable extractors.
Quick Start
pip install omni-rag-mcp
omni-rag-setup
That's it. Restart Claude Code and the plugin auto-indexes your working directory on first search.
How It Works
Your Files -> Extractors -> Chunking -> Embedding -> Qdrant (local)
|
Claude Code -> MCP Tool Call -> Hybrid Search -> Relevant Snippets
- First search auto-ingests your working directory (extracts content, chunks, generates embeddings, stores in local Qdrant)
- Subsequent searches are fast hybrid lookups (BM25 + semantic) -- no re-ingestion needed
- Incremental updates detect git changes and only re-embed modified files
MCP Tools
| Tool | Purpose |
|---|---|
search |
Hybrid search over indexed files (auto-ingests if needed) |
search_by_file |
Search filtered by file path pattern |
get_context |
Compressed directory overview (languages, structure, dependencies) |
get_file_signatures |
Function/class signatures without reading every file |
get_dependency_graph |
Internal import/dependency graph |
stats |
Index size and configuration |
ingest |
Manual re-index (incremental by default, force=True for full) |
check_status |
Is the index current? Any uncommitted changes? |
Embedding Providers
Zero-config by default. Choose your provider:
| Provider | Config | Notes |
|---|---|---|
| ONNX (default) | None needed | Auto-downloads all-MiniLM-L6-v2 (23MB, 384-dim) |
| Ollama | OMNI_RAG_EMBEDDING_PROVIDER=ollama |
Requires Ollama running with model pulled |
| OpenAI | OMNI_RAG_EMBEDDING_PROVIDER=openai + OMNI_RAG_OPENAI_API_KEY=sk-... |
text-embedding-3-small |
| Voyage | OMNI_RAG_EMBEDDING_PROVIDER=voyage + OMNI_RAG_VOYAGE_API_KEY=... |
voyage-code-3 (optimized for code) |
Optional Extras
pip install omni-rag-mcp[pdf] # PDF extraction (PyMuPDF)
pip install omni-rag-mcp[docx] # Word document extraction
pip install omni-rag-mcp[image] # Image/OCR extraction (Tesseract + Pillow)
pip install omni-rag-mcp[all] # All optional extractors
Storage
By default, uses Qdrant in local/on-disk mode -- no Docker needed. Data stored in .omni-rag/ under your project directory.
For remote Qdrant:
OMNI_RAG_QDRANT_MODE=remote
OMNI_RAG_QDRANT_HOST=your-host
OMNI_RAG_QDRANT_PORT=6333
Configuration
All settings via environment variables with OMNI_RAG_ prefix. See config/.env.example for the full reference.
Legacy RAG_ prefix variables are still supported with deprecation warnings.
Development
# Install with dev dependencies
pip install -e ".[dev]"
# Run tests
python -m pytest tests/ -v
# Health check
python scripts/health_check.py
Manual MCP Registration
If omni-rag-setup doesn't work, add this to your Claude Code MCP config:
{
"mcpServers": {
"omni-rag": {
"command": "omni-rag"
}
}
}
Install Omni Rag in Claude Desktop, Claude Code & Cursor
unyly install omni-rag-mcpInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add omni-rag-mcp -- uvx omni-rag-mcpFAQ
Is Omni Rag MCP free?
Yes, Omni Rag MCP is free — one-click install via Unyly at no cost.
Does Omni Rag need an API key?
No, Omni Rag runs without API keys or environment variables.
Is Omni Rag hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Omni Rag in Claude Desktop, Claude Code or Cursor?
Open Omni Rag on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
Related MCPs
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
by modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
by xuzexin-hzCompare Omni Rag with
Not sure what to pick?
Find your stack in 60 seconds
Author?
Embed badge for your README
Browse similar
All ai MCPs
