minimax-llm-mcp

minimax_tool_call

Pass tools and tool_choice to MiniMax M3 for native tool-use support. Returns assistant responses with structured tool call proposals when the model requests tool execution.

Instructions

M3-native tool-use passthrough. Forwards tools and tool_choice verbatim to MiniMax M3 and returns the assistant content plus any proposed tool_calls. When the upstream finishes with finish_reason 'tool_calls', the text content is a structured JSON block with the call list.

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": {
      "messages": "<messages>",
      "tools": "<tools>"
    },
    "name": "minimax_tool_call"
  }
}

Input Schema

Name	Required	Default
`stop`	No
`user`	No
`model`	No	MiniMax-M3
`tools`	Yes
`top_p`	No
`messages`	Yes
`max_tokens`	No
`temperature`	No
`tool_choice`	No
`presence_penalty`	No
`frequency_penalty`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 25, 2026

TDQS

A3.7/5.0

Behavior3/5

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

With no annotations provided, the description bears full responsibility. It explains the forwarding behavior and return content, but omits details like authentication needs, rate limits, error handling, or side effects. The description is partially transparent but leaves notable gaps.

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 long, front-loads the core purpose, and contains no redundant words. Every sentence adds essential information, achieving maximal efficiency.

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?

Given 11 parameters, no output schema, and no annotations, the description is insufficient. It explains the core mechanism but fails to document most parameters, return value format (beyond mentioning a JSON block), or error conditions. The agent lacks full context to use the tool correctly.

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

Parameters2/5

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

Schema coverage is 0%, so the description must compensate. It only explains that 'tools' and 'tool_choice' are forwarded verbatim, adding value for those two parameters. However, 9 other parameters (stop, user, model, top_p, max_tokens, temperature, etc.) receive no explanation, resulting in very limited parameter context.

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 states it is a 'tool-use passthrough' for MiniMax M3, specifies it forwards `tools` and `tool_choice` verbatim, and returns assistant content and tool calls. This distinguishes it from sibling tools (minimax_chat, minimax_complete, minimax_count_tokens) by focusing on tool invocation.

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 context for when to use this tool (when handling tool calls from MiniMax M3) by mentioning the finish_reason 'tool_calls' behavior. However, it does not explicitly state when not to use it or name direct alternatives, though sibling names imply the choice.

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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