Which integrations are available for this server?

Enables comprehensive web research using Google's Gemini Deep Research Agent via the MCP server.

How do I use gemini-deep-research-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@gemini-deep-research-mcp research the latest developments in quantum computing and their potential impact on cryptography" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

gemini-deep-research-mcp

by bharatvansh

Overview Schema Related Servers Score Discussions

Python

Remote

Gemini Deep Research MCP

PyPI version npm version License: MIT

An MCP server that exposes Gemini's Deep Research Agent for comprehensive web research.

One-Click Install

IDE	Install
Cursor
VS Code
VS Code Insiders

Note: After clicking, replace your-api-key with your Gemini API key. VS Code requires version 1.101+.

Related MCP server: Gemini Research MCP Server

Installation Methods

Using npx (Node.js)

Requires Node.js 16+ and uv.

npx @bharatvansh/gemini-deep-research-mcp

{
  "servers": {
    "gemini-deep-research": {
      "command": "npx",
      "args": ["-y", "@bharatvansh/gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "npx",
      "args": ["-y", "@bharatvansh/gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.codeium/windsurf/mcp_config.json (macOS/Linux) or %USERPROFILE%\.codeium\windsurf\mcp_config.json (Windows):

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "npx",
      "args": ["-y", "@bharatvansh/gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "npx",
      "args": ["-y", "@bharatvansh/gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.claude/settings.json:

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "npx",
      "args": ["-y", "@bharatvansh/gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.codex/config.toml:

[mcp_servers.gemini-deep-research]
command = "npx"
args = ["-y", "@bharatvansh/gemini-deep-research-mcp"]

[mcp_servers.gemini-deep-research.env]
GEMINI_API_KEY = "your-api-key"

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "npx",
      "args": ["-y", "@bharatvansh/gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to your Antigravity mcp_config.json:

{
  "gemini-deep-research": {
    "command": "npx",
    "args": ["-y", "@bharatvansh/gemini-deep-research-mcp"],
    "env": {
      "GEMINI_API_KEY": "your-api-key"
    }
  }
}

Using uvx (Python)

Requires uv.

uvx gemini-deep-research-mcp

{
  "servers": {
    "gemini-deep-research": {
      "command": "uvx",
      "args": ["gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "uvx",
      "args": ["gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.codeium/windsurf/mcp_config.json (macOS/Linux) or %USERPROFILE%\.codeium\windsurf\mcp_config.json (Windows):

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "uvx",
      "args": ["gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "uvx",
      "args": ["gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.claude/settings.json:

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "uvx",
      "args": ["gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.codex/config.toml:

[mcp_servers.gemini-deep-research]
command = "uvx"
args = ["gemini-deep-research-mcp"]

[mcp_servers.gemini-deep-research.env]
GEMINI_API_KEY = "your-api-key"

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "uvx",
      "args": ["gemini-deep-research-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to your Antigravity mcp_config.json:

{
  "gemini-deep-research": {
    "command": "uvx",
    "args": ["gemini-deep-research-mcp"],
    "env": {
      "GEMINI_API_KEY": "your-api-key"
    }
  }
}

Using pip

pip install gemini-deep-research-mcp

{
  "servers": {
    "gemini-deep-research": {
      "command": "gemini-deep-research-mcp",
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "gemini-deep-research-mcp",
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.codeium/windsurf/mcp_config.json (macOS/Linux) or %USERPROFILE%\.codeium\windsurf\mcp_config.json (Windows):

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "gemini-deep-research-mcp",
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "gemini-deep-research-mcp",
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.claude/settings.json:

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "gemini-deep-research-mcp",
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.codex/config.toml:

[mcp_servers.gemini-deep-research]
command = "gemini-deep-research-mcp"

[mcp_servers.gemini-deep-research.env]
GEMINI_API_KEY = "your-api-key"

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "gemini-deep-research": {
      "command": "gemini-deep-research-mcp",
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

Add to your Antigravity mcp_config.json:

{
  "gemini-deep-research": {
    "command": "gemini-deep-research-mcp",
    "env": {
      "GEMINI_API_KEY": "your-api-key"
    }
  }
}

Antigravity

Open the Agent side panel → click ... → MCP Store
Search for your MCP server or click Add Custom Server
Add this configuration to your mcp_config.json:

{
  "gemini-deep-research": {
    "command": "uvx",
    "args": ["gemini-deep-research-mcp"],
    "env": {
      "GEMINI_API_KEY": "your-api-key"
    }
  }
}

Prerequisites

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows (PowerShell)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Tool: `gemini_deep_research`

Conducts comprehensive web research using Gemini's Deep Research Agent. Blocks until research completes (typically 10-20 minutes).

When to use:

Complex topics requiring multi-source analysis
Synthesized information from the web
Fact-checking and cross-referencing

Parameter	Type	Required	Default	Description
`prompt`	string	✓	—	Your research question or topic
`include_citations`	boolean		`true`	Include resolved source URLs

Output	Description
`status`	`completed`, `failed`, or `cancelled`
`report_text`	Synthesized research report

Configuration

Variable	Required	Default	Description
`GEMINI_API_KEY`	✓	—	Your Gemini API key
`GEMINI_DEEP_RESEARCH_AGENT`		`deep-research-preview-04-2026`	Deep Research agent to use. Set to `deep-research-max-preview-04-2026` for maximum thoroughness, or `deep-research-preview-04-2026` for standard speed.
`GEMINI_MODEL`		`gemini-3.5-flash`	Default Gemini model fallback for other tasks.

Development

git clone https://github.com/bharatvansh/gemini-deep-research-mcp.git
cd gemini-deep-research-mcp
pip install -e .[dev]
pytest

License

MIT

Install Server

license - permissive license

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How are these scores calculated?

Maintenance

–Maintainers

–Response time

5wRelease cycle

5Releases (12mo)

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Gemini Deep Research MCP

One-Click Install

Installation Methods

Using npx (Node.js)

Using uvx (Python)

Using pip

Antigravity

Prerequisites

Tool: gemini_deep_research

Configuration

Development

License

Maintenance

Resources

Looking for Admin?

Tools

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Langgraph Deep Search MCP

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Related MCP Connectors

Appeared in Searches

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MCP directory API

Tool: `gemini_deep_research`