claude-max-mcp

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ask_claude

Delegate complex tasks to Claude for code generation, reasoning, and engineering. Include all context in the prompt, as Claude has no conversation memory.

Instructions

Delegate a substantive task to Claude Code, billed against the user's Claude Max / Pro subscription (model: claude-opus-4-7). Use this for: code generation, deep reasoning, multi-step engineering, refactoring, or anything that needs more capability than the routing model can reliably deliver. The receiver has NO memory of the calling agent's conversation — include everything Claude needs in the prompt argument: the user's verbatim request, project / file context, relevant prior messages, and what kind of output you want back. Returns Claude's full text response.

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": {
      "prompt": "<prompt>"
    },
    "name": "ask_claude"
  }
}

Input Schema

Name	Required	Description	Default
`prompt`	Yes	The full prompt to send to Claude. Claude has no access to the calling agent's conversation — include all context here.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Jun 11, 2026

TDQS

A4.8/5.0

Behavior4/5

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

No annotations are provided, so the description must carry the full burden. It discloses key behaviors: no memory of conversation, billing against subscription, and the model used. It lacks details on potential rate limits or response format beyond 'full text response', but overall is transparent.

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 extremely concise—two sentences—with no wasted words. It front-loads the core purpose and then provides essential usage guidance. Every sentence earns its place.

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?

Given the tool has only one parameter and no output schema, the description is fully complete. It explains the tool's purpose, when to use it, how to structure the input, and the key behavioral constraint (no memory). No additional information is necessary for correct invocation.

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

Parameters5/5

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

Schema coverage is 100% for the single parameter. The description adds significant meaning: it explains why the prompt must contain all context (no conversation access) and what elements it should include, going well beyond the schema's basic description.

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 the tool's purpose: delegating tasks to Claude Code. It specifies the model (claude-opus-4-7) and the subscription billing context, and contrasts with the routing model, providing strong clarity even without sibling tools.

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?

The description explicitly lists when to use the tool (code generation, deep reasoning, multi-step engineering, refactoring) and what to include in the prompt (user request, context, prior messages, desired output). It also warns that Claude has no conversation memory, guiding correct usage.

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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