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Hypernym MCP Server

Hypernym MCP Server

Local
github.com/bmorphismAI & Agents6Updated 82w ago

About Hypernym MCP Server

Hypernym MCP Server exposes Hypernym AI semantic analysis and compression for LLMs and agents. It supports stdio and HTTP/HTTPS JSON-RPC access, with tools for text analysis and semantic compression.

Key features

  1. 01Semantic text categorization and analysis
  2. 02Meaning-preserving text compression
  3. 03Compression metrics and similarity thresholds
  4. 04stdio and HTTP/HTTPS JSON-RPC interfaces
  5. 05Exponential backoff for API retries

Use cases

  1. 01Generate semantic categories and compression metrics for text
  2. 02Compress text while retaining its core meaning
  3. 03Extract key details from complex text

MCP support

The MCP server exposes Hypernym AI capabilities through `analyze_text` and `semantic_compression` tools. MCP clients can connect over stdio or HTTP/HTTPS JSON-RPC.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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!

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.