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MindManager MCP Server

MindManager MCP Server

by robertZaufall
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

serialize_current_mindmap_to_markdown

Convert your current mind map to Markdown format with options for notes inclusion, detail levels, and text-only export.

Instructions

Serializes the currently loaded mindmap to Markdown format.

Args:
    include_notes (bool): If True, include notes in the serialization. Defaults to True.
    mode (str): Detail level ('full', 'content', 'text'). Defaults to 'content'.
    turbo_mode (bool): Enable turbo mode (text only). Defaults to False.

Returns:
    Union[str, Dict[str, str]]: Markdown formatted string or error dictionary.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "serialize_current_mindmap_to_markdown"
  }
}

Input Schema

NameRequiredDescriptionDefault
include_notesNo
modeNocontent
turbo_modeNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "result": {
+      "anyOf": [
+        {
+          "type": "string"
+        },
+        {
+          "additionalProperties": {
+            "type": "string"
+          },
+          "type": "object"
+        }
+      ],
+      "title": "Result"
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "title": "serialize_current_mindmap_to_markdownOutput",
+  "type": "object"
+}
  2. First observed

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions the tool serializes a 'currently loaded mindmap' (implying state dependency) but doesn't cover error conditions, performance implications, or what 'turbo mode' entails beyond 'text only'. More context on these aspects would improve transparency.

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 well-structured and front-loaded with the core purpose, followed by parameter and return details. It uses bullet-like formatting for clarity without unnecessary verbosity, though the 'Args' and 'Returns' sections could be integrated more seamlessly.

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 moderate complexity (3 parameters, state dependency) and no annotations, the description is partially complete. It covers parameters and return types (aided by an output schema), but lacks usage context, error handling details, and behavioral nuances like how 'mode' and 'turbo_mode' interact, leaving gaps for an agent.

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 description adds meaningful semantics beyond the input schema, which has 0% coverage (no descriptions for parameters). It explains 'include_notes' controls note inclusion, 'mode' defines detail levels with examples ('full', 'content', 'text'), and 'turbo_mode' enables text-only output. This compensates well for the schema's lack of documentation.

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

Purpose5/5

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

The description clearly states the specific action ('serializes') and resource ('currently loaded mindmap') with the output format ('to Markdown format'). It distinguishes from sibling tools like 'serialize_current_mindmap_to_json' and 'serialize_current_mindmap_to_mermaid' by specifying the target format.

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?

No guidance is provided on when to use this tool versus alternatives like the JSON or Mermaid serialization siblings. The description lacks context about prerequisites (e.g., needing a loaded mindmap) or scenarios favoring Markdown output over other formats.

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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