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Git Metrics MCP Server

Git Metrics MCP Server

by jonmatum
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_technical_debt

Analyze a git repository to detect technical debt indicators such as stale code and risky development patterns.

Instructions

Identify technical debt indicators

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": {
      "repo_path": "<repo_path>"
    },
    "name": "get_technical_debt"
  }
}

Input Schema

NameRequiredDescriptionDefault
repo_pathYesPath to git repository
stale_daysNoDays without changes to consider stale, default 90

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.7/5.0
Behavior1/5

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

No annotations are provided, and the description fails to disclose any behavioral traits such as whether this is a read-only operation, what permissions are needed, or side effects. The description carries the full burden and is completely silent.

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 a single concise sentence. It is appropriately front-loaded for a simple tool, though it could be slightly expanded without becoming verbose.

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

Completeness2/5

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

Given no output schema and two parameters, the description lacks context on what 'technical debt indicators' means or what the return value contains. There are clear gaps for a moderately capable tool.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides, but does not need to since the schema is sufficient.

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 it identifies technical debt indicators, a specific verb+resource. However, it does not differentiate from sibling tools like get_quality_metrics, which may have overlapping purpose.

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 vs alternatives, nor any exclusions or prerequisites. As a result, an AI agent lacks context for appropriate selection.

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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