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Rai220

Think MCP Tool

by Rai220

think

Capture and log structured thoughts during complex reasoning or multi-step tasks without altering data or obtaining new information. Ideal for AI agents needing explicit thought tracking.

Instructions

Use the tool to think about something. It will not obtain new information or change the database, but just append the thought to the log. Use it when complex reasoning or some cache memory is needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thoughtYesA thought to think about.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The 'think' tool handler: decorated with @mcp.tool(), defines an async function that takes a 'thought' parameter validated by Pydantic Field and simply returns the thought string, acting as a reasoning scratchpad.
    @mcp.tool()
    async def think(thought: str = Field(..., description="A thought to think about.")) -> str:
        """Use the tool to think about something. 
    It will not obtain new information or change the database, but just append the thought to the log. 
    Use it when complex reasoning or some cache memory is needed."""
        return thought
  • Input schema for the 'think' tool: uses Pydantic Field for the 'thought' parameter, marked as required with a description.
    async def think(thought: str = Field(..., description="A thought to think about.")) -> str:
  • Registration of the 'think' tool using the @mcp.tool() decorator on the FastMCP instance.
    @mcp.tool()
Behavior4/5

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

With no annotations provided, the description carries the full burden. It clearly discloses behavioral traits: 'It will not obtain new information or change the database, but just append the thought to the log,' indicating it's a non-destructive, logging-only operation. This adds useful context beyond the schema, though it could detail more about the log format or persistence.

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?

The description is appropriately sized with three sentences that are front-loaded: the first states the purpose, the second clarifies behavior, and the third provides usage context. There's minimal waste, though it could be slightly more structured for clarity.

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?

Given the tool's low complexity (one parameter, no annotations, but has an output schema), the description is complete enough. It covers purpose, behavior, and usage, and since an output schema exists, it needn't explain return values. However, it could benefit from more detail on the log mechanism or examples.

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?

The input schema has 100% description coverage, with the parameter 'thought' well-documented. The description adds no additional parameter semantics beyond what the schema provides, such as format or examples for the thought. Given high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.

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

Purpose3/5

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

The description states the tool is used 'to think about something' and 'append the thought to the log,' which provides a basic purpose. However, it's vague about what 'think' entails operationally and doesn't distinguish from siblings (though none exist). It avoids tautology by adding context about appending to a log, but lacks specificity in verb+resource clarity.

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

Usage Guidelines3/5

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

The description provides implied usage guidelines by stating 'Use it when complex reasoning or some cache memory is needed,' which gives context for when to invoke it. However, it lacks explicit alternatives or exclusions, and since there are no sibling tools, this guidance is minimal but adequate for basic direction.

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

Install Server

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