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central-mcp

central-mcp

by andy5090
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_user_preferences

Retrieve your saved user preferences and available preference sections to review existing rules before updating or merging new settings.

Instructions

Return the current content of ~/.central-mcp/user.md and the available preference sections.

The file holds only user-authored rules — there is no scaffolded template, so an empty content means "no preferences set yet". The response also carries available_sections (valid section values for update_user_preferences) and examples (a hint of what the user might want to set, surfaced when the user asks what's configurable). Call this before update_user_preferences so you can merge new rules with anything already saved.

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": "get_user_preferences"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.20.0

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses that the file holds user-authored rules, that empty content means no preferences, and that the response includes available_sections and examples. This is good but doesn't explicitly state the operation is read-only (though 'Return' implies it) or mention any error conditions. Still, it provides solid behavioral context.

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 well-structured: first sentence states the core action, second paragraph explains the file semantics and response fields, third sentence gives the usage context. Every sentence adds value without fluff, and the key info is front-loaded.

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 has no parameters and an output schema exists (though not shown), the description covers the essential semantics: file location, content interpretation, response fields, and the relationship to update_user_preferences. It's complete for a simple getter, though it doesn't elaborate on all output schema details, which is acceptable.

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 tool has zero parameters, so the schema is trivially covered. The baseline for 0 params is 4, and the description doesn't need to add parameter details. It does implicitly describe the output fields, but that's separate.

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 returns the content of a specific file (~/.central-mcp/user.md) and lists the available preference sections. It also names the sibling it complements (update_user_preferences), making its purpose unambiguous and distinguishing it from other tools.

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?

It explicitly instructs to call this tool before update_user_preferences to merge new rules with existing ones, and mentions when it's useful (when the user asks what's configurable). This gives clear when-to-use guidance and implies a workflow.

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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