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merterbak

Grok MCP

by merterbak
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Python

web_search

Read-only

Perform agentic real-time web searches that analyze images and synthesize answers with citations across multiple turns.

Instructions

Answer a query using agentic real-time web search.

Grok browses the web across multiple turns, optionally inspecting images on
pages, then synthesizes an answer with citations.

Args:
    prompt: Search query or research question.
    model: Grok model used to drive the agent (default `grok-4.3`).
    allowed_domains: Restrict search to these domains (max 5, mutually exclusive with excluded).
    excluded_domains: Exclude these domains from search (max 5).
    enable_image_understanding: Let the agent analyze images it encounters.
    enable_image_search: Let the agent search for and return image results.
    include_inline_citations: Embed `[1]`-style citation markers into the answer text.
    max_turns: Cap the agent's reasoning/tool turns.

Returns:
    Markdown with the answer body followed by a `**Sources:**` list of cited URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
modelNogrok-4.3
allowed_domainsNo
excluded_domainsNo
enable_image_understandingNo
enable_image_searchNo
include_inline_citationsNo
max_turnsNo

Tool Definition Quality

A4.6/5.0
Behavior5/5

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

Discloses key behaviors beyond the readOnlyHint annotation: multi-turn browsing, image inspection, citation embedding, and return format. Provides a comprehensive picture of the tool's operation.

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?

Concise two-paragraph structure with a clear purpose statement, followed by well-organized Args list and Returns section. Every sentence adds value with no redundancy.

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?

Covers inputs (all parameters) and outputs (markdown with sources), but lacks information on error handling, rate limits, or discrimination from similar tools. Sufficient for a read-only search tool given annotations.

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

Parameters4/5

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

Despite 0% schema description coverage, the tool description lists and explains all 8 parameters, including mutual exclusivity of allowed/excluded_domains, defaults, and constraints. Adds meaningful context 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?

Clearly states 'Answer a query using agentic real-time web search', specifies verb, resource, and agentic behavior. Distinguishes from sibling tools like x_search and chat by emphasizing multi-turn browsing and citation synthesis.

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?

Describes the tool's capability (real-time web search with multi-turn browsing) and how it works, but does not explicitly state when not to use it or mention alternatives to help the agent decide between web_search and siblings like chat or x_search.

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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