Codebase Rag Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Codebase Rag Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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.
pip install omni-rag-mcp
omni-rag-setupThat's it. Restart Claude Code and the plugin auto-indexes your working directory on first search.
Your Files -> Extractors -> Chunking -> Embedding -> Qdrant (local)
|
Claude Code -> MCP Tool Call -> Hybrid Search -> Relevant Snippets| 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? |
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) |
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 extractorsBy 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=6333All 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.
# Install with dev dependencies
pip install -e ".[dev]"
# Run tests
python -m pytest tests/ -v
# Health check
python scripts/health_check.pyIf omni-rag-setup doesn't work, add this to your Claude Code MCP config:
{
"mcpServers": {
"omni-rag": {
"command": "omni-rag"
}
}
}~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.