Gemini Research MCP Server

Research Deep

research_deep

Read-only

Conduct autonomous multi-source research to answer questions, compare options, and synthesize findings for exploratory or competitive analysis.

Instructions

Comprehensive autonomous research agent. Takes 3-20 minutes.

Uses the fast/default April 2026 Deep Research agent. Use this by default for interactive questions, exploratory research, competitive analysis, comparisons, and latency/cost-sensitive multi-source synthesis.

For maximum-comprehensiveness research, use research_deep_max instead.

For vague queries, the tool automatically asks clarifying questions to refine the research scope before starting (when elicitation is available).

Input Schema

Name	Required	Description	Default
`query`	Yes	Research question or topic to investigate thoroughly
`mcp_servers`	No	Disabled: remote MCP is currently unreliable for Deep Research. Any non-empty value fails before network or Gemini API access.
`visualization`	No	'auto' allows the agent to include chart/diagram images in its response	off
`format_instructions`	No	Optional report format (e.g., 'executive briefing', 'comparison table')
`collaborative_planning`	No	When True, return the drafted research plan (not the final report) plus an interaction ID; call refine_research_plan afterwards to iterate on or approve the plan
`file_search_store_names`	No	Optional: Gemini File Search store names to search your own data alongside web

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.17.0Oct 24, 2026

addedInput schema / properties / collaborative_planning

Added value: +{
+  "default": false,
+  "description": "When True, return the drafted research plan (not the final report) plus an interaction ID; call refine_research_plan afterwards to iterate on or approve the plan",
+  "type": "boolean"
+}

changedInput schema / properties / mcp_servers / description

Previous value: -"Optional remote MCP server configs for Deep Research. Each item may include name, url, headers, and allowed_tools."New value: +"Disabled: remote MCP is currently unreliable for Deep Research. Any non-empty value fails before network or Gemini API access."

addedInput schema / properties / visualization

Added value: +{
+  "default": "off",
+  "description": "'auto' allows the agent to include chart/diagram images in its response",
+  "enum": [
+    "off",
+    "auto"
+  ],
+  "type": "string"
+}

First observedv0.1.0Jul 30, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered, and the description adds real value on top: a 3-20 minute latency envelope and automatic clarifying-question elicitation when the query is vague. It does not restate that mcp_servers is disabled or describe the collaborative_planning handoff, but those are carried by the schema descriptions.

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

Conciseness4/5

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

Front-loaded with purpose and latency, then the default/recommended use case, then the exclusion — good ordering for scanning. Minor waste in the model-version sentence ('fast/default April 2026 Deep Research agent') and stray line breaks, but nothing is genuinely misleading.

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?

An output schema exists so return values needn't be explained, and annotations cover the safety profile. Combined with the description's latency, use-case routing, sibling exclusion, and elicitation behavior, an agent has everything needed to decide to call it and what to expect while it runs.

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 description coverage is 100%, so the schema already documents every parameter including the disabled mcp_servers, the visualization enum, and the collaborative_planning follow-up call. The description adds only indirect param guidance (vague queries trigger elicitation) and no syntax or format detail, so the baseline 3 applies.

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?

States a specific verb+resource (autonomous research agent) with the scope-defining trait that matters most: 3-20 minute runtime. It explicitly names the sibling research_deep_max as the alternative for maximum comprehensiveness, so an agent can pick between the two without opening either schema.

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

Usage Guidelines5/5

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

Gives an explicit default rule ('use this by default for interactive questions, exploratory research, competitive analysis, comparisons, latency/cost-sensitive synthesis') plus an explicit when-not with the named substitute. It also discloses the fallback behavior for vague queries, which changes how an agent should phrase a call.

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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