Onyx MCP Server

The Onyx MCP Server bridges the gap between AI assistants that speak Model Context Protocol (MCP) and the rich semantic knowledge stored in an Onyx AI database. By exposing Onyx’s powerful search, retrieval‑augmented generation (RAG), and chat APIs through a lightweight MCP interface, the server lets developers inject domain‑specific expertise into conversational agents without rewriting custom adapters or handling raw HTTP calls. This means that an assistant can query a company’s internal documentation, policy manuals, or product specs as naturally as it would ask a human colleague.

At its core, the server implements two intuitive tools: and a chat integration that combines LLM inference with Onyx’s RAG pipeline. When a client sends a query, the search tool performs semantic matching across document sets, applies LLM‑based relevance filtering, and returns not only the best‑matching chunk but also surrounding context to preserve narrative flow. Developers can toggle between chunked results and full‑document retrieval, or narrow the search to specific document sets for higher precision. The chat tool leverages Onyx’s conversational endpoint, automatically injecting retrieved context into the LLM prompt so that answers are both grounded in the knowledge base and conversationally fluent.

Key capabilities include:

• Semantic search with relevance filtering – ensures that the most pertinent passages surface, even in large corpora.
• Context window retrieval – provides adjacent text to give the assistant a fuller understanding of each match.
• Configurable document set targeting – lets teams focus searches on relevant subsets, reducing noise and improving response times.
• Full‑document fallback – useful for policy documents or long reports where chunk boundaries might split critical information.
• Seamless integration with existing MCP clients – no extra SDKs required; just point the client to the server’s executable and set environment variables.

Real‑world scenarios where this MCP shines include enterprise knowledge management, regulatory compliance checks, and product support. For example, a customer‑support chatbot can instantly pull the latest onboarding procedures from Onyx, ensuring that answers are accurate and up‑to‑date. In a legal firm, attorneys can query precedent documents or internal policy guidelines without leaving their preferred AI interface. The server’s lightweight design also makes it ideal for on‑premises deployment, giving organizations full control over data residency and security.

In summary, the Onyx MCP Server empowers developers to turn any MCP‑compatible assistant into a domain‑aware conversational agent, leveraging Onyx’s semantic indexing and RAG engine with minimal friction. Its configurable search options, context‑rich retrieval, and tight integration with AI workflows provide a robust foundation for building intelligent, knowledge‑centric applications.