What is Unichat Ts Mcp Server

unichat-ts-mcp-server is a TypeScript-based MCP server that facilitates communication with various AI models, including OpenAI, MistralAI, Anthropic, xAI, Google AI, and DeepSeek using the MCP protocol.

Use cases

Use cases for unichat-ts-mcp-server include automated code reviews, generating documentation for codebases, explaining code functionality, and modifying existing code based on specified changes.

How to use

To use unichat-ts-mcp-server, install the necessary dependencies with ‘npm install’, build the server with ‘npm run build’, and run it using ‘npx -y unichat-ts-mcp-server’. Configure the server with your preferred model and API key in the configuration file.

Key features

Key features include support for multiple AI models, tools for code review, documentation generation, code explanation, and code reworking. It supports both STDIO and SSE transport mechanisms.

Where to use

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Unichat MCP Server in TypeScript

Also available in Python

Send requests to OpenAI, MistralAI, Anthropic, xAI, Google AI or DeepSeek using MCP protocol via tool or predefined prompts. Vendor API key required.

Both STDIO and SSE transport mechanisms supported via arguments.

Tools

The server implements one tool:

• unichat: Send a request to unichat
  • Takes “messages” as required string arguments
  • Returns a response

Prompts

• code_review
  • Review code for best practices, potential issues, and improvements
  • Arguments:
    • code (string, required): The code to review"
• document_code
  • Generate documentation for code including docstrings and comments
  • Arguments:
    • code (string, required): The code to comment"
• explain_code
  • Explain how a piece of code works in detail
  • Arguments:
    • code (string, required): The code to explain"
• code_rework
  • Apply requested changes to the provided code
  • Arguments:
    • changes (string, optional): The changes to apply"
    • code (string, required): The code to rework"

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Running evals

The evals package loads an mcp client that then runs the index.ts file, so there is no need to rebuild between tests. You can load environment variables by prefixing the npx command. Full documentation can be found here.

OPENAI_API_KEY=your-key  npx mcp-eval src/evals/evals.ts src/server.ts

Installation

Installing via Smithery

To install Unichat MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install unichat-ts-mcp-server --client claude

Installing manually

To use with Claude Desktop, add the server config:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json

Run locally:

Run published:

Runs in STDIO by default or with argument --stdio. To run in SSE add argument --sse

npx -y unichat-ts-mcp-server --sse

Supported Models:

A list of currently supported models to be used as "YOUR_PREFERRED_MODEL_NAME" may be found here. Please make sure to add the relevant vendor API key as "YOUR_VENDOR_API_KEY"

Example:

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.

If you experience timeouts during testing in SSE mode change the request URL on the inspector interface to: http://localhost:3001/sse?timeout=600000