Airweave Search
MCP server for searching Airweave collections with natural language queries.
Ask AI about Airweave Search
Powered by Claude · Grounded in docs
I know everything about Airweave Search. Ask me about installation, configuration, usage, or troubleshooting.
0/500
Reviews
Documentation
Open-source context retrieval layer for AI agents and RAG systems.
What is Airweave?
Airweave connects to your apps, tools, and databases, continuously syncs their data, and exposes it through a unified, LLM-friendly search interface. AI agents query Airweave to retrieve relevant, grounded, up-to-date context from multiple sources in a single request.
Where it fits
Airweave sits between your data sources and AI systems as shared retrieval infrastructure. It handles authentication, ingestion, syncing, indexing, and retrieval so you don't have to rebuild fragile pipelines for every agent or integration.
How it works
- Connect your apps, databases, and documents (50+ integrations)
- Airweave syncs, indexes, and exposes your data through a unified retrieval layer
- Agents query Airweave via our SDKs, REST API, MCP, or native integrations with popular agent frameworks
- Agents retrieve relevant, grounded context on demand
Quickstart
Cloud-hosted: app.airweave.ai
Self-hosted
git clone https://github.com/airweave-ai/airweave.git
cd airweave
./start.sh
Requires Docker and docker-compose
Supported Integrations
SDKs
pip install airweave-sdk # Python
npm install @airweave/sdk # TypeScript
from airweave import AirweaveSDK
client = AirweaveSDK(api_key="YOUR_API_KEY")
results = client.collections.search(
readable_id="my-collection",
query="Find recent failed payments"
)
Tech Stack
- Frontend: React/TypeScript with ShadCN
- Backend: FastAPI (Python)
- Databases: PostgreSQL (metadata), Vespa (vectors)
- Workers: Temporal (orchestration), Redis (pub/sub)
- Deployment: Docker Compose (dev), Kubernetes (prod)
Contributing
We welcome contributions! See our Contributing Guide.