Unichat (TS)
About
Integrates multiple language models via the unified Unichat tool, enabling seamless interaction across OpenAI, MistralAI, Anthropic, xAI, and Google AI platforms.
Details
- Author
- amidabuddha
- Repository
- amidabuddha/unichat-ts-mcp-server
- GitHub stars
- 11
- Downloads
- 1,583
- License
- MIT License
- Categories
- Productivity, Developer Tools, Design, Workplace, File Management, AI, Community, Frontend, API, Infrastructure, Other
Jump to
- One tool: unichat for sending chat requests
- Four predefined prompts: code review, document code, explain code, code rework
- Supports STDIO and SSE transport mechanisms
- Works with multiple AI vendors (OpenAI, MistralAI, Anthropic, xAI, Google AI, DeepSeek)
- Available as an npm package and via Smithery
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Unichat (TS)Command (node, npx, python, etc.)nodeArguments-
Argument 1
{{/path/to}}/unichat-ts-mcp-server/build/index.js
Environment-
UNICHAT_MODEL
YOUR_PREFERRED_MODEL_NAME -
UNICHAT_API_KEY
YOUR_VENDOR_API_KEY
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
To install Unichat MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install unichat-ts-mcp-server --client claude
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:
{
"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:
{
"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
npx -y unichat-ts-mcp-server --sse
SSE transport validates the Host header against localhost, 127.0.0.1, and [::1] by default. For remote SSE deployments, set MCP_ALLOWED_HOSTS to a comma-separated list of allowed hostnames.
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:
"env": {
"UNICHAT_MODEL": "gpt-5.4-mini",
"UNICHAT_API_KEY": "YOUR_OPENAI_API_KEY"
}
unichat
Send a request to unichat. Takes 'messages' as required string arguments and returns a response.
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.
The server implements one tool:
- unichat: Send a request to unichat
- Takes "messages" as required string arguments
- Returns a response
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"unichat (ts)": {
"env": {
"UNICHAT_MODEL": "YOUR_PREFERRED_MODEL_NAME",
"UNICHAT_API_KEY": "YOUR_VENDOR_API_KEY"
},
"args": [
"{{/path/to}}/unichat-ts-mcp-server/build/index.js"
],
"command": "node"
}
}
}Linux
{
"env": {
"UNICHAT_MODEL": "YOUR_PREFERRED_MODEL_NAME",
"UNICHAT_API_KEY": "YOUR_VENDOR_API_KEY"
},
"args": [
"{{/path/to}}/unichat-ts-mcp-server/build/index.js"
],
"command": "node"
}Macos
{
"env": {
"UNICHAT_MODEL": "YOUR_PREFERRED_MODEL_NAME",
"UNICHAT_API_KEY": "YOUR_VENDOR_API_KEY"
},
"args": [
"{{/path/to}}/unichat-ts-mcp-server/build/index.js"
],
"command": "node"
}Windows
{
"env": {
"UNICHAT_MODEL": "YOUR_PREFERRED_MODEL_NAME",
"UNICHAT_API_KEY": "YOUR_VENDOR_API_KEY"
},
"args": [
"{{/path/to}}/unichat-ts-mcp-server/build/index.js"
],
"command": "node"
}Unichat MCP Server in TypeScript
Also available in Python -- <h4 align="center"> <a href="https://glama.ai/mcp/servers/ub2u8wtbbv">
</a>
<a href="https://smithery.ai/server/unichat-ts-mcp-server"><br>
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
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:
{
"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:
{
"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
npx -y unichat-ts-mcp-server --sse
SSE transport validates the Host header against localhost, 127.0.0.1, and [::1] by default. For remote SSE deployments, set MCP_ALLOWED_HOSTS to a comma-separated list of allowed hostnames.
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:
"env": {
"UNICHAT_MODEL": "gpt-5.4-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, 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
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