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robertZaufall

MindManager MCP Server

get_mindmanager_version

Retrieve the current version of the MindManager application to verify compatibility and functionality with the MCP server.

Instructions

Gets the version of the MindManager application.

Returns:
    Union[str, Dict[str, str]]: The version of the MindManager application or error dictionary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The primary handler function for the 'get_mindmanager_version' tool. It is decorated with @mcp.tool() for automatic registration and schema inference from type hints and docstring. Executes mm.Mindmanager().get_version() to retrieve the version and handles exceptions using a helper.
    @mcp.tool()
    async def get_mindmanager_version(
    ) -> Union[str, Dict[str, str]]:
        """
        Gets the version of the MindManager application.
    
        Returns:
            Union[str, Dict[str, str]]: The version of the MindManager application or error dictionary.
        """
        try:
            version = mm.Mindmanager().get_version()
            print(f"get_mindmanager_version() returned: {version}", file=sys.stderr)
            return version
        except Exception as e:
            return _handle_mindmanager_error("get_mindmanager_version", e)
  • Supporting helper function used by get_mindmanager_version (and other tools) to standardize error responses from MindManager operations.
    def _handle_mindmanager_error(func_name: str, e: Exception) -> Dict[str, str]:
        """Formats MindManager errors for MCP response."""
        error_message = f"Error during MindManager operation '{func_name}': {e}"
        print(f"ERROR: {error_message}", file=sys.stderr)
        # Check for specific known errors from mindm.mindmanager if possible
        if "No document found" in str(e):
            return {"error": "MindManager Error", "message": "No document found or MindManager not running."}
        # Add more specific error checks here based on mindm library
        return {"error": "MindManager Error", "message": f"An error occurred: {e}"}
  • The @mcp.tool() decorator registers the get_mindmanager_version function with the MCP server, inferring input/output schemas from annotations and docstring.
    @mcp.tool()
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 mentions the return type (version string or error dictionary), which adds some context beyond the basic purpose. However, it does not cover other behavioral aspects like error conditions, performance, or dependencies, leaving gaps in transparency.

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 well-structured: a single sentence states the purpose, followed by a clear 'Returns' section. Every sentence adds value without waste, making it easy to parse and understand quickly.

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 (0 parameters, output schema exists), the description is complete enough for its purpose. It explains what the tool does and the return format, though it could benefit from more behavioral context (e.g., error handling). The output schema reduces the need for detailed return value explanations.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately avoids redundant parameter details, earning a high score for not cluttering with unnecessary information.

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 with a specific verb ('Gets') and resource ('version of the MindManager application'), making it immediately understandable. However, it does not explicitly differentiate from sibling tools like 'get_versions', which might serve a similar purpose, preventing a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, such as 'get_versions' or other sibling tools. It lacks context on prerequisites, timing, or exclusions, leaving the agent without usage direction.

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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