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
git clone https://github.com/bharatvansh/gemini-deep-research-mcpThis 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.
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Releases
README
Gemini Deep Research MCP
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-keywith your Gemini API key. VS Code requires version 1.101+.
Installation Methods
Using npx (Node.js)
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"
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.