How do I install the gemini embedding 2 mcp server?

Use a recorded configuration for your client, replace example credential values and paths, and verify the documented runtime. Restart or reconnect the client, then inspect the available tools.

What credentials does it need?

It reads `GEMINI_API_KEY` from the environment. Store these in your client's env block or a secrets manager — never commit them to a repository — and grant the narrowest scope that still covers your use case.

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Gemini Embedding 2 MCP Server

<strong>A multimodal local memory MCP for AI agents powered by Gemini Embedding 2.</strong>

Remote serverstreamable-httpPython

What is the Gemini Embedding 2 MCP Server?

A multimodal local memory MCP for AI agents powered by Gemini Embedding 2.

The short version

One embedding space across modalities — Search code, PDFs, images, audio, and video from the same memory layer
Local-first persistence — Your index stays in ~/.gemini_mcp_db, not in a hosted vector database
Agent-friendly retrieval — Search results include exact paths, types, modalities, and page-aware context
Zero-config by default — The server uses built-in guardrails and sensible indexing defaults so most users do not need a config file

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

How to install the Gemini Embedding 2 MCP Server

{
  "mcpServers": {
    "gemini-embedding-2-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/AlaeddineMessadi/gemini-embedding-2-mcp-server.git@v1.2.1",
        "gemini-embedding-2-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "YOUR_GEMINI_API_KEY"
      }
    }
  }
}

From the project documentation. Replace placeholders and example paths before connecting.

Configuration

Variable	Description	Required
GEMINI_API_KEY	Declared in the maintainer’s client configuration.	Check documentation

Frequently asked questions

<strong>A multimodal local memory MCP for AI agents powered by Gemini Embedding 2.</strong> Confirm the tools offered by your installed version in the connected client. Tool availability and permissions depend on the server and account configuration.