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mindnode-mcp

mindnode-mcp

by jyuwaaw
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Read a mind map

get_mindmap

Read a MindNode mind map as a Markdown outline by providing its document ID or title. Returns the root heading and nested bullets for text-based review.

Instructions

Read a mind map's content as a Markdown outline (root heading + nested bullets), reconstructed from MindNode's local store. Best-effort: heavily edited text may be imperfect — cross-check with get_mindmap_image when exactness matters.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "document": "<document>"
    },
    "name": "get_mindmap"
  }
}

Input Schema

NameRequiredDescriptionDefault
documentYesDocument reference: a documentID (UUID) or a document title

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.7/5.0
Behavior5/5

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 accurately reveals that the content is reconstructed from MindNode's local store, that the result is best-effort, and that heavily edited text may be imperfect. This goes well beyond a bare read-only statement and prepares the agent for potential fidelity issues.

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 two concise sentences with no filler. The core behavior and output format are front-loaded, and the important limitation and cross-reference to the sibling tool are placed immediately after.

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

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter read tool, the description is complete: it specifies the output format, the source of the data, the fidelity limitation, and the recommended alternative when exactness is critical. No critical decision-relevant context is missing.

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 single parameter is already fully described in the schema as a documentID or document title, so schema coverage is 100%. The tool description adds no additional parameter-specific detail, so the baseline score of 3 is appropriate.

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 a specific verb ('Read') and resource ('a mind map's content') and specifies the output format as a Markdown outline with root heading and nested bullets. It also distinguishes this from the sibling get_mindmap_image by emphasizing textual outline reconstruction rather than an image.

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

Usage Guidelines5/5

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

The description explicitly names get_mindmap_image as the alternative when exactness matters, giving the agent a clear decision rule for a common failure mode. It also implies this tool is appropriate when a Markdown outline is sufficient, even if heavily edited text may be imperfect.

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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