Unichat MCP Server

The Unichat MCP Server is a versatile bridge that lets AI assistants—such as Claude, OpenAI’s ChatGPT, or any MCP‑compatible client—talk to a wide array of language model vendors through a single, uniform interface. By exposing a unified set of tools and prompts, the server abstracts away vendor‑specific APIs, allowing developers to focus on crafting user experiences rather than handling multiple authentication flows or request formats. This is especially valuable in environments where a project must support several providers for redundancy, cost optimization, or to leverage unique model strengths.

At its core, the server implements one primary tool, , which forwards a sequence of messages to the chosen model and returns the generated reply. The tool accepts raw message strings, making it trivial to integrate into conversational agents that need to relay user input or context to a large language model. Beyond the generic tool, the server also offers a suite of predefined prompts tailored to common development workflows: , , , and . Each prompt accepts plain text arguments—such as source code or change requests—and returns a structured response. This design lets developers embed code‑centric AI helpers directly into IDEs, CI pipelines, or chat interfaces without writing custom request logic.

Key capabilities include support for both STDIO and Server‑Sent Events (SSE) transport mechanisms, giving teams flexibility in how they deploy the server—whether as a lightweight local process or a more scalable HTTP endpoint. Environment variables ( and ) let users specify the target model name and vendor key, making it straightforward to switch between providers like OpenAI, MistralAI, Anthropic, xAI, or Google AI. The server’s prompt definitions encapsulate best‑practice patterns: for example, automatically checks for style issues and potential bugs, while generates docstrings that can be injected into codebases.

Typical use cases span from automated code review bots in pull‑request workflows to interactive coding assistants embedded in editors. Teams can also use the prompt to create educational tools that walk students through complex algorithms, or leverage in continuous integration pipelines to apply automated refactorings. Because the server presents a single MCP endpoint, developers can switch vendors or adjust model parameters without touching client code—ideal for experimentation or multi‑model deployment strategies.

In summary, the Unichat MCP Server delivers a cohesive, vendor‑agnostic interface that streamlines AI integration for code‑centric tasks. Its combination of a generic messaging tool, specialized prompts, dual transport options, and simple configuration makes it an attractive choice for developers who need reliable, flexible access to multiple large‑language models within their AI workflows.