Augments AI responses with relevant documentation context through vector search.
Augments AI responses with relevant documentation context through vector search.
An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
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claude mcp add ragdocs-3 --env EMBEDDING_PROVIDER=your-value --env EMBEDDING_MODEL=your-value --env OPENAI_API_KEY=your-value --env FALLBACK_PROVIDER=your-value --env FALLBACK_MODEL=your-value --env QDRANT_URL=your-value -- npx -y kill-port| Variable | Description | Required |
|---|---|---|
| EMBEDDING_PROVIDER | Configuration value read at startup. | Optional |
| EMBEDDING_MODEL | Configuration value read at startup. | Optional |
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
| FALLBACK_PROVIDER | Configuration value read at startup. | Optional |
| FALLBACK_MODEL | Configuration value read at startup. | Optional |
| QDRANT_URL | Endpoint or connection string the server talks to. | Yes |
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