Opik MCP Server

Opik MCP Server is an open‑source Model Context Protocol (MCP) implementation that brings the full power of the Opik platform into AI‑assistant workflows. By exposing a single, protocol‑compliant interface, the server allows developers to interact with Opik’s core capabilities—prompt management, project organization, trace tracking, and metrics collection—without having to write custom integration code for each tool or environment.

The server solves the friction that normally accompanies LLM‑centric tooling: developers often need to juggle separate APIs for prompt libraries, experiment tracking, and performance monitoring. Opik MCP Server consolidates these functions into a unified API surface that any MCP‑compatible client can consume. This means an AI assistant such as Claude can, in a single request, list available prompts, create a new trace for an LLM run, or query historical metrics—all while remaining agnostic to the underlying transport mechanism.

Key features include:

• Prompt Management – Create, list, update, and delete prompts directly from the assistant’s context. This facilitates dynamic prompt selection or on‑the‑fly editing during a conversation.
• Project/Workspace Management – Organize work into logical projects, allowing the assistant to scope operations or retrieve project‑specific data without manual filtering.
• Trace Tracking – Record detailed execution traces for LLM calls, enabling later analysis or debugging. The assistant can request trace summaries or visualizations as part of a response.
• Metrics Querying – Pull aggregated performance metrics (latency, cost, accuracy) to inform decision‑making or provide feedback within the conversation.

In practice, this server is invaluable for developers building IDE extensions (e.g., Cursor), chat‑based AI assistants, or automated experiment pipelines. By integrating with the MCP ecosystem, a developer can embed Opik’s observability and prompt libraries directly into their workflow, reducing context switching and ensuring consistent data provenance. The ability to choose between transport mechanisms—stdio for local IDE integration or SSE for event‑driven scenarios—offers flexibility that adapts to deployment constraints.

Overall, Opik MCP Server provides a seamless bridge between the rich telemetry and prompt infrastructure of Opik and the conversational capabilities of modern AI assistants, enabling smarter, more context‑aware development experiences.