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mdmagic-mcp-server

by io.github.MDMagic-MCP

recommend_template

Read-onlyIdempotent

Suggest the best built-in template(s) for a described purpose. Use this when the user describes WHAT the document is (e.g. 'Q4 board pack', 'API reference', 'wedding invitation', 'legal contract') without naming a template. Returns ranked recommendations with rationale.

Why this exists: AI assistants often guess template names that don't exist. This tool maps purpose → real template names from MDMagic's catalog, so convert_document doesn't fail with 'template not found'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNNoHow many recommendations to return (1-5, default 3)
purposeYesFree-text description of the document's purpose. Examples: 'Q4 board pack for investors', 'restaurant menu', 'developer API documentation', 'wedding invitation'.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "purpose": {
-      "description": "Echoes back the purpose that was matched",
-      "type": "string"
-    },
-    "rationale": {
-      "description": "Why these templates were picked",
-      "type": "string"
-    },
-    "recommendations": {
-      "description": "Ranked list of template IDs to pass to convert_document",
-      "items": {
-        "type": "string"
-      },
-      "type": "array"
-    }
-  },
-  "required": [
-    "recommendations"
-  ],
-  "type": "object"
-}New value: +null
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context: it returns ranked recommendations with rationale, maps purpose to real template names to avoid 'template not found' errors, and is limited to built-in templates. This goes beyond the safety profile encoded in 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 concise and well-structured. It opens with a clear imperative sentence, then gives a usage condition, a return description, and a brief 'Why this exists' rationale. Every sentence earns its place, and the content is front-loaded so the core purpose is immediately clear.

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 read-only tool with two parameters, no output schema, and strong annotations, the description is fully adequate. It covers the input condition ('describes WHAT the document is'), the scope ('built-in templates'), and the return type ('ranked recommendations with rationale'). The rationale behind the tool's existence further helps an agent decide when to invoke it.

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 covers both parameters (purpose and topN) with descriptions and examples, so schema coverage is 100%. The description reinforces the purpose parameter's meaning with additional examples and the 'without naming a template' qualifier, but it adds no extra syntax, formatting, or behavioral details beyond what the schema already provides. Baseline 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 the tool's function: 'Suggest the best built-in template(s) for a described purpose.' It specifies the resource (built-in templates) and the action (recommend based on purpose). It also distinguishes itself from sibling tools like list_all_templates and convert_document by addressing the problem of guessing nonexistent template names.

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

Usage Guidelines4/5

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

The description provides an explicit trigger condition: 'Use this when the user describes WHAT the document is... without naming a template.' It explains why this tool exists and indirectly references alternatives via convert_document, but it doesn't explicitly enumerate when-not-to-use cases or name sibling alternatives for those scenarios.

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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TDQS

A4.5/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: credit balance vs cost estimation, template listing scoped to all/built-in/custom, and conversion vs validation. The three list tools are explicitly named by scope, eliminating ambiguity.

Naming Consistency5/5

All tool names follow the same verb_noun snake_case pattern (check_, convert_, estimate_, get_, list_, recommend_, show_, validate_), making the API predictable and easy to navigate.

Tool Count5/5

10 tools is well within the ideal 3-15 range for a document conversion service. Each tool addresses a necessary step in the workflow (template selection, validation, cost estimation, conversion, credit monitoring) without redundancy.

Completeness4/5

The core lifecycle (pre-flight validation, cost estimation, conversion, balance checking, template discovery) is fully covered. Minor gaps exist—no template upload or settings update—but these are likely handled outside the MCP server, so the surface is complete for its intended agent workflows.

Resources