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Git MCP Server

Git MCP Server

by yumeminami
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_merge_request_commits

Get commits for a merge request with details like SHA, message, author, and dates. Supports optional filters for specific commits.

Instructions

Get commits for a merge request

Args: platform: The platform name (e.g., 'gitlab', 'github') project_id: The project identifier mr_id: The merge request/pull request ID **filters: Optional filters for commit selection

Returns: Dict containing: - mr_id: The merge request ID - total_commits: Number of commits - commits: List of commit details with sha, message, author, dates, etc.

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": {
      "platform": "<platform>",
      "project_id": "<project_id>",
      "mr_id": "<mr_id>",
      "filters": "<filters>"
    },
    "name": "get_merge_request_commits"
  }
}

Input Schema

NameRequiredDescriptionDefault
mr_idYes
filtersYes
platformYes
project_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.5

TDQS

C2.9/5.0
Behavior2/5

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

The description does not disclose behavioral traits such as pagination, rate limits, authentication requirements, or whether it returns all commits or a subset. Given the absence of annotations, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with Args and Returns sections, which is helpful, but it is slightly verbose for a simple retrieval tool. Some sentences could be streamlined without losing meaning.

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?

The description adequately covers the return format but lacks context on usage, behavioral details, and clear parameter semantics. With no annotations and 100% required parameters, it is not fully complete but sufficient for a basic understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description lists parameters but describes 'filters' as optional despite the schema requiring it as a string. It does not explain the format or possible values for filters, and the schema itself has no descriptions (0% coverage). This lack of clarity undermines correct parameter usage.

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 explicitly states the verb 'Get' and the resource 'commits for a merge request', making the tool's purpose clear. Among sibling tools like get_merge_request_details and get_merge_request_diff, it uniquely retrieves commits, so no confusion.

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 (e.g., get_merge_request_diff for diffs, list_merge_requests for listing). There is no mention of prerequisites or context, leaving the agent to infer usage from the tool name alone.

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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