Unichat MCP Server
Send requests to OpenAI, MistralAI, Anthropic, xAI, or Google AI using MCP protocol via tool or predefined prompts. Vendor API key required
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
No tools | |
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| UNICHAT_MODEL | Yes | Selected Unichat model identifier | |
| UNICHAT_API_KEY | Yes | Your Unichat API key |
Unichat MCP Server in Python
Also available in TypeScript
Send requests to OpenAI, MistralAI, Anthropic, xAI, or Google AI using MCP protocol via tool or predefined prompts. Vendor API key required
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"
Quickstart
Install
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development/Unpublished Servers Configuration
Published Servers Configuration
Development
Building and Publishing
To prepare the package for distribution:
- Sync dependencies and update lockfile:
- Build package distributions:
This will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues with dependencies of the server.
- Extract server characteristics such as tools, resources, prompts, and required parameters.
Our directory badge helps users to quickly asses that the MCP server is safe, server capabilities, and instructions for installing the server.
Copy the following code to your README.md file: