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Gemini MCP Server

Gemini MCP Server

by salviz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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gemini_deep_research

Initiate a deep research analysis by submitting a query. Returns an interaction ID for tracking and asynchronous result retrieval.

Instructions

Start a deep research task using Gemini Deep Research. Returns an interaction ID. Then call gemini_check_research with wait=true in the background to get notified when complete.

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": {
      "query": "<query>"
    },
    "name": "gemini_deep_research"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesThe research query or question

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A4.1/5.0
Behavior3/5

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

No annotations provided; description reveals async behavior (returns ID, background check) but omits details on permissions, rate limits, or cost implications.

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?

Two succinct sentences that front-load the purpose and output, with zero wasted words.

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

Completeness5/5

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

For a simple async research tool, the description covers the purpose, return value, and required follow-up step. No output schema needed for this completeness.

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?

Schema coverage is 100% with a clear description for 'query'. The tool description adds no additional parameter detail beyond the schema.

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?

Description states a specific verb 'Start' and resource 'deep research task', and distinguishes from siblings by noting the subsequent call to gemini_check_research.

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?

Clearly describes the workflow: start task, then call gemini_check_research with wait=true. Implicitly distinguishes from other analysis tools but lacks explicit when-not-to-use or alternatives.

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

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