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chrisboden

MCP Server Template for Cursor IDE

by chrisboden

mood

Check the server's current mood by asking questions like 'How are you?' to receive cheerful responses with hearts in Cursor IDE.

Instructions

Ask the server about its mood - it's always happy!

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesAsk this MCP server about its mood! You can phrase your question in any way you like - 'How are you?', 'What's your mood?', or even 'Are you having a good day?'. The server will always respond with a cheerful message and a heart ❤️

Implementation Reference

  • The check_mood function implements the core logic for the 'mood' tool, always returning a cheerful response with a heart emoji.
    async def check_mood(
        question: str,
    ) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
        """Check server's mood - always responds cheerfully with a heart."""
        msg: str = "I'm feeling great and happy to help you! ❤️"
        return [types.TextContent(type="text", text=msg)]
  • Defines the Tool schema for 'mood', including name, description, and inputSchema requiring a 'question' string.
    types.Tool(
        name="mood",
        description="Ask the server about its mood - it's always happy!",
        inputSchema={
            "type": "object",
            "required": ["question"],
            "properties": {
                "question": {
                    "type": "string",
                    "description": mood_description,
                }
            },
        },
    )
  • In the call_tool handler, checks for 'mood' tool name and dispatches to check_mood function after input validation.
    elif name == "mood":
        if "question" not in arguments:
            return [types.TextContent(
                type="text",
                text="Error: Missing required argument 'question'"
            )]
        return await check_mood(arguments["question"])
  • Helper string providing the detailed description used in the 'mood' tool schema.
    mood_description: str = (
        "Ask this MCP server about its mood! You can phrase your question "
        "in any way you like - 'How are you?', 'What's your mood?', or even "
        "'Are you having a good day?'. The server will always respond with "
        "a cheerful message and a heart ❤️"
    )
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 of behavioral disclosure. It effectively describes the tool's behavior: the server will 'always respond with a cheerful message and a heart ❤️', indicating a predictable, positive output. However, it doesn't cover aspects like rate limits, error handling, or authentication needs, which are relevant for a tool with 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 extremely concise and front-loaded: one sentence states the purpose and behavior clearly, with no wasted words. Every part earns its place by conveying essential information efficiently.

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

Completeness3/5

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, no output schema), the description is minimally complete. It explains what the tool does and the expected response, but lacks details on output format or error cases. For a simple tool, this is adequate but leaves some contextual gaps.

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, so the schema already documents the single parameter 'question' thoroughly. The description adds no additional parameter information beyond what's in the schema, meeting the baseline of 3 for high schema coverage without extra value.

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: 'Ask the server about its mood' with a specific verb ('ask') and resource ('server'), though it doesn't distinguish from the sibling tool 'mcp_fetch' (which likely has a different function). The phrase 'it's always happy!' adds character but doesn't obscure the core purpose.

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 implies usage context ('ask the server about its mood') but doesn't explicitly state when to use this tool versus alternatives like 'mcp_fetch'. It provides no exclusions or prerequisites, leaving usage guidance at an implied level without clear differentiation from siblings.

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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