What is Hypernym Mcp Server

Hypernym MCP Server is a semantic text analysis and compression tool powered by Hypernym AI, designed to provide insights and metrics on textual data.

Use cases

Use cases include summarizing lengthy documents, improving readability of technical content, generating concise reports, and enhancing search engine optimization through semantic text compression.

How to use

To use Hypernym MCP Server, input the desired text along with optional parameters for compression ratio and semantic similarity. The server will return a comprehensive analysis or a compressed version of the text while preserving its meaning.

Key features

Key features include full semantic analysis of text, categorization, compression metrics, and the ability to compress text while maintaining semantic meaning.

Where to use

Hypernym MCP Server can be utilized in various fields such as content creation, data analysis, natural language processing, and any domain requiring efficient text management.

Hypernym MCP Server

A Model Context Protocol (MCP) server providing semantic text analysis and compression tools via Hypernym AI’s API. This server allows LLMs to access Hypernym’s semantic categorization and compression capabilities through standardized MCP interfaces.

What is Hypernym AI?

Hypernym AI offers advanced semantic analysis tools that can:

• Categorize text into precise semantic buckets
• Generate adaptive compression while maintaining meaning
• Provide similarity scoring for content density
• Extract key details from complex text

Signup!

Learn more about how Hypernym helps your agents to stop losing context and overpaying for it at our Documentation

And sign up for our API waitlist (self serve coming soon!) at the link here!

Features

• Implements the Model Context Protocol (MCP) specification
• Provides MCP tools for text analysis and semantic compression
• Supports both standard MCP CLI interface through stdio transport
• Offers HTTP/HTTPS JSON-RPC 2.0 endpoints via Express
• Includes retry logic with exponential backoff for API requests
• HTTPS support for secure connections
• Properly formatted MCP tool descriptions and schemas

Installation

1. Clone the repository:

   git clone https://github.com/hypernym/hypernym-mcp-server.git
   cd hypernym-mcp-server
   

2. Install dependencies:

   npm install
   

3. Create a .env file:

   touch .env
   

4. Add your Hypernym API key and URL to the .env file:

   HYPERNYM_API_URL=https://fc-api-development.hypernym.ai
   HYPERNYM_API_KEY=your_api_key_here
   PORT=3000
   

Setting up HTTPS (recommended for production)

Generate self-signed certificates for development:

npm run generate-certs

Or provide your own certificates and update the paths in .env:

SSL_KEY_PATH=/path/to/your/server.key
SSL_CERT_PATH=/path/to/your/server.crt

Usage

1. Build the project:

   npm run build
   

2. Start the server:

   a. HTTP/HTTPS mode:

   npm start
   

   The server will start on port 3000 by default (or the port specified in your .env file).

   b. stdio transport mode (for MCP integration):

   npm run start:stdio
   

   This is the mode you should use when configuring the server in a .mcp.json file.

MCP Tools

The server provides the following tools through the Model Context Protocol:

analyze_text

Full semantic analysis of text including categorization and compression metrics.

Parameters:

• text (required): The input text to analyze
• min_compression_ratio (optional): Target compression ratio (0.0-1.0, default: 0.5)
  • 1.0 = no compression
  • 0.8 = 20% compression
  • 0.5 = 50% compression
  • 0.0 = maximum compression
• min_semantic_similarity (optional): Minimum semantic similarity threshold (0.0-1.0, default: 0.8)
  • Higher values preserve more original meaning

Returns:
Complete JSON analysis including semantic categories, compression metrics, and reconstructed text.

semantic_compression

Direct text compression that maintains semantic meaning.

Parameters:

• text (required): The input text to compress
• min_compression_ratio (optional): Target compression ratio (0.0-1.0, default: 0.5)
• min_semantic_similarity (optional): Minimum semantic similarity threshold (0.0-1.0, default: 0.8)

Returns:
Only the compressed text that preserves core meaning while maintaining readability.

Environment Variables

• HYPERNYM_API_URL (required): URL for the Hypernym API (default: https://fc-api-development.hypernym.ai)
• HYPERNYM_API_KEY (required): Your Hypernym AI API key
• PORT (optional): Port to run the server on (default: 3000)
• SSL_KEY_PATH (optional): Path to SSL key file
• SSL_CERT_PATH (optional): Path to SSL certificate file
• MCP_USE_STDIO (optional): Set to ‘true’ to force stdio transport mode

MCP Integration

To use this server with MCP-compatible AI platforms, add the following configuration to your .mcp.json file:

{
  "mcpServers": {
    "hypernym": {
      "type": "stdio",
      "command": "cd /path/to/hypernym-mcp-server && npm run start:stdio",
      "description": "Hypernym semantic analysis and compression tool",
      "tools": [
        "analyze_text",
        "semantic_compression"
      ]
    }
  }
}

This allows AI models to access Hypernym’s capabilities through MCP’s standardized tool interface.

HTTP Endpoints

The server exposes these HTTP endpoints:

• POST / - MCP JSON-RPC 2.0 endpoint for tool calls and listings
• POST /analyze_sync - Direct Hypernym API passthrough
• GET /health - Health check endpoint

Testing

Test the server with provided sample texts:

# Test server health
npm run test:server

# Test direct API endpoint
npm run test:analyze

# Test MCP semantic compression
npm run test:semantic

# Test MCP analyze_text
npm run test:analyze-mcp

JSON-RPC 2.0 Examples

List available tools:

{
  "jsonrpc": "2.0",
  "id": "1",
  "method": "tools/list"
}

Call the semantic_compression tool:

{
  "jsonrpc": "2.0",
  "id": "2",
  "method": "tools/call",
  "params": {
    "name": "semantic_compression",
    "arguments": {
      "text": "Your text to compress here",
      "min_compression_ratio": 0.5,
      "min_semantic_similarity": 0.8
    }
  }
}

API Response Example

When using the analyze_text tool, you’ll receive a JSON response like:

{
  "metadata": {
    "version": "0.1.0",
    "timestamp": "2024-03-21T00:00:00Z",
    "tokens": {
      "in": 1000,
      "out": 500,
      "total": 1500
    }
  },
  "response": {
    "meta": {
      "embedding": {
        "version": "0.1.0",
        "dimensions": 512
      }
    },
    "texts": {
      "compressed": "Philosophy::subject=existence;theme=mortality",
      "suggested": "To be or not to be - an examination of human mortality and the consequences of action versus inaction."
    },
    "segments": [
      {
        "was_compressed": true,
        "semantic_category": "Philosophical contemplation of existence",
        "semantic_similarity": 0.81,
        "compression_ratio": 0.61
      }
    ]
  }
}

For more information on the Hypernym API or to obtain an API key, contact the Hypernym team at this link here!