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Gemini Search

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Enables web search using Google Gemini with search grounding and question-answering on local documents, with support for chunked document reading.

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About

Enables web search using Google Gemini with search grounding and question-answering on local documents, with support for chunked document reading.

README

PyPI version npm version CI Tests License: MIT

Gemini Search MCP packages a Model Context Protocol server that exposes five tools:

  • web_search – Uses Gemini with Google Search grounding to answer general questions.
  • document_question_answering – Converts local documents to captioned markdown and asks Gemini to answer questions about their contents.
  • get_document_content – Converts a document to markdown and returns the full content for reading.
  • get_document_chunk – Retrieves specific chunks of large documents for easier processing.
  • get_next_chunk – Automatically continues reading from where you left off (stateful).

Installation

Python (pip)

pip install gemini-search-mcp

Node.js (npm)

npm install -g gemini-search-mcp

Usage

Set your Google API key (must have Gemini access):

export GOOGLE_API_KEY="your-key"

Run the MCP server (defaults to stdio transport):

gemini-search-mcp run
# or simply
# gemini-search-mcp

Configure Codex automatically (writes to ~/.codex/config.toml by default):

gemini-search-mcp configure --api-key "YOUR_KEY"

Configure Copilot CLI (writes to ~/.copilot/config.json):

gemini-search-mcp configure --cli-type copilot --api-key "YOUR_KEY"

Configure both Codex and Copilot CLI at once:

gemini-search-mcp configure --cli-type both --api-key "YOUR_KEY"

For npm/npx installation with custom command:

gemini-search-mcp configure --command npx --command-args -y gemini-search-mcp --api-key "YOUR_KEY"

Clear cached conversion artifacts:

gemini-search-mcp clear-cache
# 선택 옵션: --cache-dir /custom/path --remove-root

Development

Install in editable mode with testing dependencies:

pip install -e .

Ensure LibreOffice is installed and on PATH if you plan to convert non-PDF documents.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Publishing

For maintainers: See PUBLISHING.md for instructions on how to publish new versions to PyPI and npm.

Changelog

See CHANGELOG.md for a list of changes in each version.

License

MIT – all rights reserved.

from github.com/MIMICLab/GeminiSearchMCP

Install Gemini Search in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install gemini-search-mcp

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add gemini-search-mcp -- npx -y gemini-search-mcp

FAQ

Is Gemini Search MCP free?

Yes, Gemini Search MCP is free — one-click install via Unyly at no cost.

Does Gemini Search need an API key?

No, Gemini Search runs without API keys or environment variables.

Is Gemini Search hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Gemini Search in Claude Desktop, Claude Code or Cursor?

Open Gemini Search on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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