Embeddings MCP Server

A Model Context Protocol (MCP) server for generating text embeddings using OpenAI, Anthropic, or Ollama. Built with Next.js and the Vercel AI SDK, designed for easy deployment on Vercel.

Features

• Multiple Providers: Support for OpenAI, Anthropic, and Ollama embedding models

• Two Tools: Single text embedding and batch text embeddings

• Easy Deployment: Ready for deployment on Vercel

• Local Testing: Built-in support for Ollama for local development

• TypeScript: Fully typed for better developer experience

• Comprehensive Tests: Full test coverage

Related MCP server: MCP Boilerplate

Quick Start

1. Clone and install dependencies:

   git clone <your-repo>
   cd embeddings-mcp-ts
   pnpm install

2. Configure environment variables:

   cp .env.example .env.local

   Edit .env.local with your preferred provider settings.

3. Run locally:

   pnpm dev

4. Deploy to Vercel:

   npx vercel

Configuration

Environment Variables

Provider-Specific Setup

OpenAI

export EMBEDDING_PROVIDER=openai
export OPENAI_API_KEY=your_api_key_here
export OPENAI_EMBEDDING_MODEL=text-embedding-3-small

Anthropic

export EMBEDDING_PROVIDER=anthropic  
export ANTHROPIC_API_KEY=your_api_key_here

Ollama (Local Testing)

export EMBEDDING_PROVIDER=ollama
export OLLAMA_BASE_URL=http://localhost:11434
export OLLAMA_EMBEDDING_MODEL=nomic-embed-text

Make sure Ollama is running locally:

ollama serve
ollama pull nomic-embed-text

MCP Tools

embed_text

Generates an embedding for a single text string.

Parameters:

• text (string): The text to generate an embedding for

Returns:

{
  "embedding": [0.1, -0.2, 0.3, ...],
  "model": "text-embedding-3-small",
  "usage": {
    "prompt_tokens": 10,
    "total_tokens": 10
  },
  "dimensions": 1536
}

embed_texts

Generates embeddings for multiple text strings.

Parameters:

• texts (string[]): Array of texts to generate embeddings for

Returns:

{
  "embeddings": [[0.1, -0.2, ...], [0.3, -0.4, ...]],
  "model": "text-embedding-3-small", 
  "usage": {
    "prompt_tokens": 20,
    "total_tokens": 20
  },
  "count": 2,
  "dimensions": 1536
}

Claude Desktop Integration

To use this MCP server with Claude Desktop, add the following to your Claude Desktop configuration:

{
  "mcpServers": {
    "embeddings": {
      "command": "npx",
      "args": ["mcp-handler", "http://localhost:3000/api/mcp"],
      "env": {
        "EMBEDDING_PROVIDER": "openai",
        "OPENAI_API_KEY": "your_api_key_here"
      }
    }
  }
}

For production deployment, replace localhost:3000 with your Vercel deployment URL.

Development

Running Tests

pnpm test
pnpm test:watch

Type Checking

pnpm type-check

Linting

pnpm lint

Building

pnpm build

Deployment

Vercel Deployment

1. Configure environment variables in Vercel:

   • Go to your Vercel project settings

   • Add environment variables for your chosen provider

   • Set EMBEDDING_PROVIDER to your preferred provider

2. Deploy:

   npx vercel

3. Update your MCP client configuration with the deployment URL.

Architecture

• src/app/api/mcp/route.ts: Main MCP server endpoint

• src/lib/config.ts: Configuration management

• src/lib/embedding-service.ts: Provider factory

• src/lib/providers/: Individual provider implementations

• src/types/: TypeScript type definitions

License

MIT