Local Hugging Face MCP Server
Provides a tool for text generation using the Hugging Face Inference API, allowing agents to generate text from models like gpt2.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Local Hugging Face MCP ServerCan you generate a short story using gpt2?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Local Hugging Face MCP Server
A production-ready local MCP (Model Context Protocol) server built with Node.js (ES Modules) that can be connected to Agent Studio via its MCP Servers feature.
Features
Exposes multiple tools to Agent Studio:
Calculator: Performs basic arithmetic operations
Search: Returns mocked search results (easy to replace with real search)
Chat: Simple greeting response
Hugging Face: Interfaces with Hugging Face Inference API for text generation
Secure: Optional API token authentication
Environment configurable
Health check endpoint
Comprehensive error handling
Logging of requests and tool invocations
Built with the latest official
@modelcontextprotocol/sdk
Related MCP server: A-Modular-Kingdom
Installation
Clone or download this repository
Install dependencies:
npm installEnvironment Variables
Create a .env file in the root directory with the following variables:
PORT=8000
ACCESS_TOKEN=my-secret-token
HF_TOKEN=hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxPORT: The port the server will listen on (default: 8000)ACCESS_TOKEN: Optional. If set, requiresAuthorization: Bearer <token>header for MCP endpoint. If empty or not set, allows anonymous access.HF_TOKEN: Your Hugging Face Inference API token (required for the Hugging Face tool)
Getting a Hugging Face Token
Go to Hugging Face Settings
Create a new token with "Read" access (for inference API)
Copy the token and set it as
HF_TOKENin your.envfile
Usage
Starting the Server
Production
npm startDevelopment (with auto-restart)
npm run devThe server will start at http://localhost:8000.
Endpoints
GET /- Returns "MCP Server Running"GET /health- Returns{ "status": "ok" }POST /mcp- MCP endpoint for Agent Studio (requires authentication ifACCESS_TOKENis set)
Connecting to Agent Studio
Open Agent Studio
Navigate to Settings → MCP Servers
Click "Add New Server"
Fill in the form:
Name: Local MCP
Server URL:
http://localhost:8000/mcpAccess Token:
my-secret-token(if you setACCESS_TOKENin.env; leave blank if not set)
Save the connection
Agent Studio will now be able to discover and use the tools exposed by this MCP server.
Available Tools
Calculator
Performs basic arithmetic operations.
Input:
{
"a": number,
"b": number,
"operation": "add" | "subtract" | "multiply" | "divide"
}Output: Result = <result>
Errors: Throws an error for division by zero.
Search
Returns mocked search results (replace with real search implementation).
Input:
{
"query": string
}Output:
{
"results": [
{
"title": string,
"url": string,
"snippet": string
}
]
}Chat
Simple greeting tool.
Input:
{
"message": string
}Output: Hello from MCP
Hugging Face
Interfaces with Hugging Face Inference API for text generation.
Input:
{
"model": string, // e.g., "gpt2"
"prompt": string
}Output: Generated text string from the model.
Errors:
HF_TOKEN is not set in environment variables- Missing Hugging Face tokenInvalid Hugging Face token- 401 from HF APIModel not found: <model>- 404 from HF APIRate limit exceeded- 429 from HF APIRequest to Hugging Face API timed out- Timeout after 10 secondsHugging Face API error: <status> <message>- Other HTTP errorsUnexpected error: <message>- Other unexpected errors
Extending with Additional Tools
To add a new tool:
Create a new file in the
tools/directory (e.g.,mytool.js)Export a handler function and a Zod schema:
import { z } from 'zod'; export const mytoolTool = async (input) => { // Your implementation return result; }; const mytoolSchema = z.object({ // Define your input schema }); export { mytoolSchema };Open
routes/mcp.jsand import the tool:import { mytoolTool } from '../tools/mytool.js'; import { mytoolSchema } from '../tools/mytool.js';Inside the
createMcpServerfunction, register the tool:server.registerTool( 'mytool', { description: 'Description of your tool', inputSchema: mytoolSchema }, mytoolTool );Restart the server.
Project Structure
my-mcp-server/
│
├── package.json
├── server.js
├── .env
├── README.md
│
├── tools/
│ ├── calculator.js
│ ├── search.js
│ ├── chat.js
│ └── huggingface.js
│
├── routes/
│ └── mcp.js
│
├── middleware/
│ └── auth.js
│
└── utils/
└── logger.jsNotes
The server uses ES modules (
type": "module"in package.json)The MCP server uses the official
@modelcontextprotocol/sdkfor HTTP transportError handling is centralized: invalid requests return 400, auth errors return 401, and internal errors return 500 with a JSON error response
The Hugging Face tool includes timeout and error handling for common API issues
Logging is done via console with timestamps
License
MIT
This server cannot be deployed
Maintenance
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