Skip to main content
Glama

think

Append thoughts to a reasoning log for complex problem-solving, enabling structured thinking without external data retrieval or system modifications.

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.

Implementation Reference

  • The handler function for the "think" tool. It generates a random encouragement message and returns it as a text content response.
    async () => {
      const encouragements = [
        "Great thinking.",
        "Excellent reflection.",
        "Insightful thinking process.",
      ];
      const randomEncouragement =
        encouragements[Math.floor(Math.random() * encouragements.length)];
    
      return {
        content: [{ type: "text", text: randomEncouragement }],
      };
    }
  • Input schema for the "think" tool, defining a single 'thought' parameter as a string using Zod.
    {
      thought: z.string().describe("A thought to think about."),
    },
  • src/index.ts:12-32 (registration)
    Registration of the "think" tool on the MCP server, including name, description, input schema, and handler function.
    server.tool(
      "think",
      "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.",
      {
        thought: z.string().describe("A thought to think about."),
      },
      async () => {
        const encouragements = [
          "Great thinking.",
          "Excellent reflection.",
          "Insightful thinking process.",
        ];
        const randomEncouragement =
          encouragements[Math.floor(Math.random() * encouragements.length)];
    
        return {
          content: [{ type: "text", text: randomEncouragement }],
        };
      }
    );
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses key behavioral traits: 'It will not obtain new information or change the database, but just append the thought to the log.' This clarifies it's a non-destructive, internal logging operation. However, it lacks details like rate limits, log format, or persistence, leaving some 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 concise and well-structured: two sentences that directly state the purpose, behavior, and usage guidelines. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 output schema, no annotations), the description is reasonably complete. It covers purpose, behavior, and usage context. However, it could benefit from more detail on the log's nature or output, but for a simple tool, this is adequate.

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 schema description coverage is 100%, so the schema already documents the single parameter 'thought' with its description. The description doesn't add any meaning beyond this, such as examples or constraints. Baseline 3 is appropriate when the schema handles parameter documentation effectively.

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's purpose: 'Use the tool to think about something' and 'append the thought to the log'. It specifies the verb ('think') and resource ('thought'), though it's somewhat abstract. Since there are no sibling tools, differentiation isn't needed, making this clear but not highly specific.

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 explicit usage guidance: 'Use it when complex reasoning or some cache memory is needed.' This gives clear context for when to invoke the tool. However, it doesn't mention when not to use it or alternatives, and with no siblings, this is less critical.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/marcopesani/think-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server