MiniMax Search MCP Server

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browse

Provide a list of URLs and a detailed query; the tool visits each page and uses language AI to answer based on the content.

Instructions

Explore specific information in a list of urls. The parameters are a url list and a query. The urls will be browsed, and each content will be sent to a Large Language Model (LLM) as the based information to answer the query.

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": {
      "urls": "<urls>",
      "query": "<query>"
    },
    "name": "browse"
  }
}

Input Schema

Name	Required	Description	Default
`urls`	Yes	The url list.
`query`	Yes	The query. A detailed natural language query is recommended.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 13, 2026

TDQS

B3.2/5.0

Behavior3/5

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

The description discloses that URLs are browsed and content is sent to an LLM to answer the query, which is a key behavioral trait. However, it lacks details on side effects, permissions, rate limits, or privacy implications, which are needed given no annotations.

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 concise with two sentences that front-load the purpose and then explain the operation. No redundant or extraneous information is present.

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

Completeness2/5

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

The description does not explain the output format or return value, nor does it address potential errors, timeouts, or limitations. Given the lack of an output schema, this is a significant omission for a tool that fetches URLs.

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%, and the description adds a recommendation for a detailed natural language query. However, the description largely restates the parameter names without adding significant new meaning beyond the schema.

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

Purpose4/5

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

The description clearly states the tool explores specific information from a list of URLs using a query and an LLM. However, it does not explicitly differentiate the tool from its sibling 'search', which may lead to ambiguity.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives, nor any conditions or prerequisites. The description simply explains the tool's operation without contextual usage advice.

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

Deploy Server

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