# Gemini DeepSearch

> Use this tool when you need to perform in-depth web research with automated citation tracking and source attribution. Gemini DeepSearch solves problems related to comprehensive information synthesis, fact-checking, and gathering current information beyond training data through systematic web exploration. It takes in research queries and effort level configurations, and outputs synthesized answers with proper source attribution, making it ideal for research tasks requiring thorough information gathering and verification.

Canonical page: https://skillsregistry.net/skills/alexcong-gemini-deepsearch  
JSON: https://api.skillsregistry.net/v1/skills/alexcong-gemini-deepsearch

## Description

This MCP server provides automated multi-step web research capabilities using Google Gemini models and Google Search API to perform deep information gathering with citation tracking. Built by Alex Cong using Python with LangGraph workflow orchestration, FastMCP integration, and Google's generative AI tools, it implements a sophisticated research agent that generates diverse search queries, conducts parallel web searches, reflects on knowledge gaps through iterative loops, and synthesizes final answers with proper source attribution. The implementation offers configurable effort levels (low/medium/high) that control research depth through query count and loop iterations, supports both HTTP API and stdio MCP deployment modes, and includes LangGraph Studio integration for workflow visualization, making it valuable for research tasks requiring comprehensive information synthesis, fact-checking with source verification, and scenarios where AI assistants need to gather current information beyond their training data through systematic web exploration.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/alexcong-gemini-deepsearch)
- **Repository:** <https://github.com/alexcong/gemini-deepsearch-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "alexcong-gemini-deepsearch"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alexcong-gemini-deepsearch` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alexcong-gemini-deepsearch/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt