About Airweave Search
Airweave Search is an MCP server for querying Airweave collections in natural language. Airweave is an open-source context retrieval layer that syncs data from many apps and databases for AI agents and RAG systems.
Key features
- 01Natural language search over Airweave collections
- 02Unified, LLM-friendly retrieval interface
- 03Continuous syncing and indexing of sources
- 0450+ data source integrations
Use cases
- 01Giving AI agents grounded context from several sources
- 02Providing shared retrieval infrastructure for RAG systems
MCP support
The project is an MCP server that exposes natural language search over Airweave collections to MCP clients.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://mcp.airweave.ai/mcpclaude mcp add --transport http airweave-ai-search https://mcp.airweave.ai/mcp{"mcpServers":{"airweave-ai-search":{"type":"http","url":"https://mcp.airweave.ai/mcp"}}}Open in Cursor{"servers":{"airweave-ai-search":{"type":"http","url":"https://mcp.airweave.ai/mcp"}}}Open in VS Code{"mcpServers":{"airweave-ai-search":{"type":"http","url":"https://mcp.airweave.ai/mcp"}}}{"mcpServers":{"airweave-ai-search":{"serverUrl":"https://mcp.airweave.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://mcp.airweave.ai/mcpAuth requiredTools
Details
From the project README
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.instant(
readable_id="my-collection",
query="Find recent failed payments"
)
CLI
Search collections, manage sources, and trigger syncs from your terminal:
pip install airweave-cli
airweave auth login
airweave search "quarterly revenue figures" --collection finance-data
The CLI outputs rich interactive results in your terminal and clean JSON when piped — making it work for both developers and AI agents.
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.
License
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.