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MyBlockcities

MCP Server Template for Cursor IDE

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 is the core handler for the 'mood' tool. It ignores the question and always returns a cheerful message 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)]
  • Input schema definition for the 'mood' tool, specifying an object with a required 'question' string property.
    inputSchema={
        "type": "object",
        "required": ["question"],
        "properties": {
            "question": {
                "type": "string",
                "description": mood_description,
            }
        },
    },
  • Registration of the 'mood' tool in the list_tools handler, including name, description, and schema.
    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,
                }
            },
        },
    )
  • Dispatch logic in the call_tool handler that routes 'mood' tool calls to the 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 constant providing the detailed description used in the mood tool's input 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 ❤️"
    )
Behavior3/5

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 reveals key traits: the server will 'always respond with a cheerful message and a heart ❤️' and 'it's always happy!' which discloses predictable behavior. However, it doesn't mention rate limits, authentication needs, or other operational constraints that would be helpful for a complete behavioral picture.

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 (one sentence) and front-loaded with the core purpose. Every word earns its place - 'Ask the server about its mood' establishes function, and 'it's always happy!' adds useful behavioral context without redundancy.

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 simplicity (single parameter, no output schema, no annotations), the description provides adequate context. It explains what the tool does and the predictable response behavior. For a straightforward mood inquiry tool, this is reasonably complete, though it could benefit from mentioning the response format more explicitly.

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?

Schema description coverage is 100%, so the schema already fully documents the single 'question' parameter with examples. The description doesn't add any parameter-specific information beyond what's in the schema. This meets the baseline of 3 for high schema coverage where the description doesn't need to compensate.

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' - a specific verb ('Ask') and resource ('server's mood'). It distinguishes from the sibling tool 'mcp_fetch' by focusing on mood inquiry rather than data fetching. However, it doesn't explicitly contrast with the sibling, keeping it at 4 instead of 5.

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 through 'it's always happy!' which suggests this is for cheerful interactions, but doesn't provide explicit guidance on when to use this versus alternatives. No when-not-to-use scenarios or comparison to sibling tools is mentioned, leaving usage somewhat implied rather than clearly defined.

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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