Unichat MCP Server
# Unichat MCP Server in Python
Also available in [TypeScript](https://github.com/amidabuddha/unichat-ts-mcp-server)
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Send requests to OpenAI, Anthropic, and OpenAI-compatible providers using MCP protocol via tool or predefined prompts. For OpenAI-compatible providers such as MistralAI, xAI, Google AI, DeepSeek, Alibaba, or Inception, set `UNICHAT_BASE_URL` to the provider's compatible API endpoint.
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`
**Supported Models:**
> A list of currently supported models to be used as `"SELECTED_UNICHAT_MODEL"` may be found [here](https://github.com/amidabuddha/unichat/blob/main/unichat/models.py). Please make sure to add the relevant vendor API key as `"YOUR_UNICHAT_API_KEY"`
**Example:**
```json
"env": {
"UNICHAT_MODEL": "gpt-5.4-mini",
"UNICHAT_API_KEY": "YOUR_OPENAI_API_KEY"
}
```
For OpenAI-compatible providers with custom endpoints:
```json
"env": {
"UNICHAT_MODEL": "PROVIDER_MODEL",
"UNICHAT_API_KEY": "YOUR_PROVIDER_API_KEY",
"UNICHAT_BASE_URL": "https://provider.example.com/v1"
}
```
When `UNICHAT_BASE_URL` is set, the server accepts the configured `UNICHAT_MODEL` without checking it against Unichat's built-in model list.
Development/Unpublished Servers Configuration
```json
"mcpServers": {
"unichat-mcp-server": {
"command": "uv",
"args": [
"--directory",
"{{your source code local directory}}/unichat-mcp-server",
"run",
"unichat-mcp-server"
],
"env": {
"UNICHAT_MODEL": "SELECTED_UNICHAT_MODEL",
"UNICHAT_API_KEY": "YOUR_UNICHAT_API_KEY"
}
}
}
```
Published Servers Configuration
```json
"mcpServers": {
"unichat-mcp-server": {
"command": "uvx",
"args": [
"unichat-mcp-server"
],
"env": {
"UNICHAT_MODEL": "SELECTED_UNICHAT_MODEL",
"UNICHAT_API_KEY": "YOUR_UNICHAT_API_KEY"
}
}
}
```
### Installing via Smithery
To install Unichat for Claude Desktop automatically via [Smithery](https://smithery.ai/server/unichat-mcp-server):
```bash
npx -y @smithery/cli install unichat-mcp-server --client claude
```
## Development
### Building and Publishing
To prepare the package for distribution:
1. Remove older builds:
```bash
rm -rf dist
```
2. Sync dependencies and update lockfile:
```bash
uv sync
```
3. Build package distributions:
```bash
uv build
```
This will create source and wheel distributions in the `dist/` directory.
4. Publish to PyPI:
```bash
uv publish --token {{YOUR_PYPI_API_TOKEN}}
```
### Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging
experience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector).
You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:
```bash
npx @modelcontextprotocol/inspector uv --directory {{your source code local directory}}/unichat-mcp-server run unichat-mcp-server
```
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
## Hosted deployment
A hosted deployment is available on [Fronteir AI](https://fronteir.ai/mcp/amidabuddha-unichat-mcp-server).
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'unichat' has a clear and distinct purpose of chatting with an assistant.
A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'unichat' follows a simple, readable pattern without any conflicting conventions.
A single tool is too few for most server purposes, as it severely limits functionality and scope. While it might be appropriate for a minimal chat interface, it feels thin and lacks the depth expected for a typical MCP server, which usually requires multiple tools to handle different operations or resources.
For a chat assistant domain, the single tool 'unichat' covers the core action of chatting, but there are notable gaps. It lacks operations for managing chat history, configuring settings, or handling multiple sessions, which are common in chat systems. However, the basic functionality is present, allowing agents to perform the primary task.