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MCP server for searching Airweave collections
MCP server for searching Airweave collections
Open-source context retrieval layer for AI agents and RAG systems.
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.
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.
git clone https://github.com/airweave-ai/airweave.git
cd airweave
./start.sh
Requires Docker and docker-compose
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"
)
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.
We welcome contributions! See our Contributing Guide.
Выполни в терминале:
claude mcp add airweave-mcp-search --env AIRWEAVE_API_KEY="" --env AIRWEAVE_BASE_URL="" --env AIRWEAVE_COLLECTION="" -- npx -y airweave-mcp-searchWeb content fetching and conversion for efficient LLM usage.
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolProvides auto-configuration for setting up an MCP server in Spring Boot applications.
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
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