MCP Server
About
# MCP Server A simple **Node.js** server that acts as a proxy for interacting with **LM Studio** models. It provides two API endpoints: - Fetch available models - Perform chat completions Built using **Express.js**, **Axios**, and **Body-parser**. --- ## 🚀 Features - Fetch available models from LM Studio (`GET…
Explore
- Fetch available models from LM Studio (GET /v1/models)
- Perform chat completions with selected models (POST /v1/chat/completions)
- Built-in CORS support for cross-origin API access
- Simple and easy to extend
---
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
MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
1. Clone the repository:
git clone https://github.com/master-faraz-official/mcp-server.git
cd mcp-server
2. Install dependencies:
npm install
---
1. Make sure LM Studio is running locally at http://localhost:11434.
2. Start the server:
node index.js
> The server will run at
http://localhost:3000
---
- Node.js
- Express.js
- Axios
- Body-parser
- CORS
---
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp server": {
"Node.js-MCP-Server": {
"command": "node",
"args": [
"index.js"
]
}
}
}
}McpServers
{
"Node.js-MCP-Server": {
"command": "node",
"args": [
"index.js"
]
}
}A simple Node.js server that acts as a proxy for interacting with LM Studio models.
It provides two API endpoints:
- Fetch available models
- Perform chat completions
Built using Express.js, Axios, and Body-parser.
---
🚀 Features
- Fetch available models from LM Studio (GET /v1/models)
- Perform chat completions with selected models (POST /v1/chat/completions)
- Built-in CORS support for cross-origin API access
- Simple and easy to extend
---
📦 Installation
1. Clone the repository:
git clone https://github.com/master-faraz-official/mcp-server.git
cd mcp-server
2. Install dependencies:
npm install
---
🛠 Usage
1. Make sure LM Studio is running locally at http://localhost:11434.
2. Start the server:
node index.js
> The server will run at
http://localhost:3000
---
📚 API Endpoints
1. Fetch Models
GET /v1/models
Fetches a list of available models from LM Studio.
Example Response:
{
"object": "list",
"data": [
{
"id": "model-id-1",
"object": "model",
"owned_by": "local"
}
]
}
2. Chat Completion
POST /v1/chat/completions
Send a chat conversation and get a model's response.
Request Body:
{
"model": "your-model-id",
"messages": [
{ "role": "user", "content": "Hello!" }
],
"temperature": 0.7
}
Example Response:
{
"id": "chatcmpl-abc123",
"object": "chat.completion",
"created": 1714150000,
"model": "your-model-id",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! How can I assist you today?"
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 0,
"completion_tokens": 0,
"total_tokens": 0
}
}
---
⚙️ Environment Details
- Node.js
- Express.js
- Axios
- Body-parser
- CORS
---
📄 Notes
- Ensure that LM Studio is running on your local machine (localhost:11434).
- The server acts as a bridge, formatting the responses in an OpenAI-compatible format.
---
📜 License
This project is open source and available under the MIT License.
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