Skip to main content
Glama
Ray0907

Git MCP Server

by Ray0907

list_comments

Retrieve all comments on a GitHub or GitLab issue or pull request to review discussions and track feedback.

Instructions

List all comments on an issue or pull request

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesRepository identifier (GitLab: "group/project" or ID, GitHub: "owner/repo")
typeYesType of item
numberYesIssue or PR number
sortNoSort order
pageNoPage number (default: 1)
per_pageNoItems per page (default: 20, max: 100)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the basic action but lacks crucial behavioral details: it doesn't mention pagination behavior (implied by 'page' and 'per_page' parameters but not explained), rate limits, authentication requirements, or what the output format looks like. For a list operation with 6 parameters, this is insufficient.

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 a single, clear sentence that states the core functionality without unnecessary words. It's front-loaded and efficiently communicates the essential purpose, earning its place fully.

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 the complexity (6 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain the return values, pagination behavior, or any constraints like rate limits. For a list operation that likely returns structured data, more context is needed to help an agent use it effectively.

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 all parameters are documented in the schema. The description adds no additional parameter information beyond implying the tool works on 'issue or pull request' (which aligns with the 'type' parameter). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.

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 the verb ('List') and resource ('comments on an issue or pull request'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_issue' or 'get_pull_request', which might also return comment data, but the focus on listing comments specifically is clear.

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 versus alternatives. For example, it doesn't mention whether 'get_issue' or 'get_pull_request' might include comments, or if this is the primary way to retrieve comment data. There's no context about prerequisites or limitations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Ray0907/git-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server