npm package: @fastmcp-me/unichat-ts-mcp-server
Description: Unichat MCP Server
Author: Stefan
Latest version: 0.2.8

[![Add to Cursor](https://fastmcp.me/badges/cursor_dark.svg)](https://fastmcp.me/MCP/Details/542/unichat-ts)
[![Add to VS Code](https://fastmcp.me/badges/vscode_dark.svg)](https://fastmcp.me/MCP/Details/542/unichat-ts)
[![Add to Claude](https://fastmcp.me/badges/claude_dark.svg)](https://fastmcp.me/MCP/Details/542/unichat-ts)
[![Add to ChatGPT](https://fastmcp.me/badges/chatgpt_dark.svg)](https://fastmcp.me/MCP/Details/542/unichat-ts)
[![Add to Codex](https://fastmcp.me/badges/codex_dark.svg)](https://fastmcp.me/MCP/Details/542/unichat-ts)
[![Add to Gemini](https://fastmcp.me/badges/gemini_dark.svg)](https://fastmcp.me/MCP/Details/542/unichat-ts)



# Unichat MCP Server in TypeScript
Also available in [Python](https://github.com/amidabuddha/unichat-mcp-server)
--
 <h4 align="center">
  <a href="https://glama.ai/mcp/servers/ub2u8wtbbv"><img width="380" height="200" src="https://glama.ai/mcp/servers/ub2u8wtbbv/badge" alt="unichat-ts-mcp-server MCP server" /></a>
  <a href="https://mseep.ai/app/amidabuddha-unichat-ts-mcp-server"><img width="380" height="200" src="https://mseep.net/pr/amidabuddha-unichat-ts-mcp-server-badge.png" alt="MseeP.ai Security Assessment Badge" /></a>
  <a href="https://smithery.ai/server/unichat-ts-mcp-server"><br>
  <img src="https://smithery.ai/badge/unichat-ts-mcp-server" alt="Smithery Server Installations" />
  </a>
</h4>

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:
```bash
npm install
```

Build the server:
```bash
npm run build
```

For development with auto-rebuild:
```bash
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](https://www.mcpevals.io/docs).

```bash
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](https://smithery.ai/server/unichat-ts-mcp-server):

```bash
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:
```json
{
  "mcpServers": {
    "unichat-ts-mcp-server": {
      "command": "node",
      "args": [
        "{{/path/to}}/unichat-ts-mcp-server/build/index.js"
      ],
      "env": {
        "UNICHAT_MODEL": "YOUR_PREFERRED_MODEL_NAME",
        "UNICHAT_API_KEY": "YOUR_VENDOR_API_KEY"
      }
    }
}
```
Run published:
```json
{
  "mcpServers": {
    "unichat-ts-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "unichat-ts-mcp-server"
      ],
      "env": {
        "UNICHAT_MODEL": "YOUR_PREFERRED_MODEL_NAME",
        "UNICHAT_API_KEY": "YOUR_VENDOR_API_KEY"
      }
    }
}
```


> Runs in STDIO by default or with argument `--stdio`. To run in SSE add argument `--sse`
```bash
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](https://github.com/amidabuddha/unichat-ts/blob/main/src/models.ts). Please make sure to add the relevant vendor API key as `"YOUR_VENDOR_API_KEY"`

**Example:**
```json
"env": {
  "UNICHAT_MODEL": "gpt-4o-mini",
  "UNICHAT_API_KEY": "YOUR_OPENAI_API_KEY"
}
```
### Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector), which is available as a package script:

```bash
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