1. Conduid
  2. Developer Tools
  3. Gemini Deep Research MCP
MCP server · Developer Tools

Gemini Deep Research MCP

This MCP server that brings Gemini's Deep Research Agent to the AI coding assistants. This provides ai assistant with very high quality deep web research. Ai coding assisstant when doing deep research on their own easily fill up their context size, but gemini makes it very very efficient. the only negative is time and pricing here.

53Fair

Scored a month ago · breakdown

About Gemini Deep Research MCP

Gemini Deep Research MCP is an MCP server published by bharatvansh in the Developer Tools category: this MCP server that brings Gemini's Deep Research Agent to the AI coding assistants. This provides ai assistant with very high quality deep web research. Ai coding assisstant when doing deep research on their own easily fill up their context size, but gemini makes it very very efficient. the only negative is time and pricing here.

The repository has 4 stars and 1 forks, with the last commit 2 months ago. Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/bharatvansh/gemini-deep-research-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Ask AI

✦

Ask AI about Gemini Deep Research MCP

Powered by Claude · Grounded in docs

I know everything about Gemini Deep Research MCP. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

Static checks derived from the repository 3 days ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • !License declaredNo license file. Legally you have no right to use it in a product.
  • ✓Tests presentA test suite exists in the repository.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

v0.2.0v0.2.0 · 21 Aug 2026🚀 What's New in v0.2.0 ⚡ Non-Blocking Async MCP Tools Split the previous blocking research tool into two asynchronous MCP tools to prevent client timeouts during long research jobs: `start_deep_research`: Dispatches the research task and…
v0.1.4v0.1.4 · 18 Jun 2026Updated the deep research model to latest available from google.
v0.1.3v0.1.3 · 4 Feb 2026
0.1.20.1.2 · 2 Feb 2026
0.1.10.1.1 · 2 Feb 2026

README

Gemini Deep Research MCP

PyPI version npm version

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

One-Click Install

IDE Install
Cursor Install in Cursor
VS Code Install in VS Code
VS Code Insiders Install in VS Code Insiders

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


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

  1. Open the Agent side panel → click ... → MCP Store
  2. Search for your MCP server or click Add Custom Server
  3. 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"

Tools

1. start_deep_research

Initiates a deep, multi-step web research job in the background using Google's Deep Research Agent. Returns a job_id, which you can use to check the status of completion using check_deep_research(job_id=...).

Parameter Type Required Default Description
prompt string ✓ — Your comprehensive research question or topic
Output Description
job_id Unique tracking ID for the research job
status Initial job state (e.g. in_progress)

2. check_deep_research

Checks the status of a Deep Research job using its job_id and returns the complete report once finished.

Parameter Type Required Default Description
job_id string ✓ — The research tracking ID from start_deep_research
include_citations boolean true Include source URLs in the report
Output Description
job_id The tracking ID of the research job
status Exact current job state (in_progress, completed, failed, or cancelled)
report_text Synthesized markdown research report (when completed)
uptime Elapsed time while the job is in progress, when available
error Failure details, when the API provides them

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.

Development

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

License

MIT

README fetched from the repository 3 days ago. The original is authoritative.

Questions

About Gemini Deep Research MCP

How do I install Gemini Deep Research MCP?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Gemini Deep Research MCP safe to use with an AI agent?

Its trust score is 53 out of 100 (fair). It passes 4 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Gemini Deep Research MCP still maintained?

Yes — the latest release is v0.2.0 (21 Aug 2026), and the last commit was 2 months ago. The repository has 4 stars.