Google Gemini MCP

Gemini Deep Research

gemini_deep_research

Conduct iterative multi-step research on complex topics, synthesizing findings into comprehensive reports.

Instructions

Conduct deep research on complex topics using iterative multi-step analysis with Gemini. This performs multiple searches and synthesizes comprehensive research reports (takes several minutes). [MCP_RECOMMENDED_TIMEOUT_MS: 900000]

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "research_question": "<research_question>"
    },
    "name": "gemini_deep_research"
  }
}

Input Schema

Name	Required	Description
`model`	No	Model to use for deep research (defaults to latest available)
`focus_areas`	No	Optional: specific areas to focus the research on
`max_iterations`	No	Number of research iterations (1-10, default 1). Environment guidance: Claude Desktop: use 1-2 (4-min timeout). Agent SDK/IDEs (VSCode, Cursor, Windsurf)/AI platforms (Cline, Roo-Cline): can use 5-7 (longer timeout tolerance)
`research_question`	Yes	The complex research question or topic to investigate deeply

Output Schema

Name	Required	Description	Default
`content`	Yes
`success`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.6.2Aug 22, 2026

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden of explaining behavior. It discloses that the tool performs multiple searches, synthesizes reports, and takes several minutes, including a recommended timeout. This is solid transparency for common behavioral concerns, even if it does not mention output format or potential failure modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences and front-loads the core purpose and approach. Every sentence adds value, and the recommended timeout is embedded in a compact, parseable tag rather than verbose prose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a complex tool with an output schema, and the description covers the key behavioral side: iterative searches, report synthesis, and time requirement. It could say a bit more about what types of comprehensive reports are produced, but the output schema likely covers return-shape expectations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides 100% description coverage for all four parameters, so the baseline is 3. The description does not add extra parameter-level detail beyond what the schema supplies, but it reinforces that research_question should be complex and that the process is iterative.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as conducting deep research on complex topics with iterative multi-step analysis, which uses a specific verb and resource. This distinguishes it from sibling tools like gemini_chat and gemini_prompt_assistant by emphasizing multiple searches and comprehensive research reports.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: complex topics requiring deep research, multiple searches, and comprehensive reports. It does not explicitly name alternatives for simpler queries, but the emphasis on complex topics and multi-step iteration makes the intended use case reasonably clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server