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Azure DevOps MCP Server

Azure DevOps MCP Server

by Tiberriver256
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_pull_request_comments

Fetch comments from a pull request in Azure DevOps using repository and pull request IDs, with optional filters for thread, count, or deleted comments.

Instructions

Get comments from a specific pull request

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": {
      "repositoryId": "<repositoryId>",
      "pullRequestId": "<pullRequestId>"
    },
    "name": "get_pull_request_comments"
  }
}

Input Schema

NameRequiredDescriptionDefault
topNoMaximum number of threads/comments to return
threadIdNoThe ID of the specific thread to get comments from
projectIdNoThe ID or name of the project (Default: MyProject)
repositoryIdYesThe ID or name of the repository
pullRequestIdYesThe ID of the pull request
includeDeletedNoWhether to include deleted comments
organizationIdNoThe ID or name of the organization (Default: mycompany)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states 'get comments' without mentioning important behaviors like pagination (top parameter), inclusion of deleted comments, or the ability to filter by threadId. The schema contains these details, but the description does not highlight them.

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 very concise (6 words), but brevity comes at the expense of completeness. While it is not verbose, it could include more detail without becoming excessively long.

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 that there is no output schema and the tool has 7 parameters (2 required), the description should explain what the tool returns (e.g., list of comments) and possibly the structure. It does not, nor does it clarify the role of optional parameters like threadId or includeDeleted.

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 has 100% description coverage, so the parameters are already documented. The description adds no extra meaning beyond the schema, earning a baseline score of 3.

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 action (get) and resource (comments from a specific pull request). It differentiates from siblings like add_pull_request_comment (write) and get_pull_request (PR details). However, it could be more precise by noting that it can also retrieve comments from a specific thread.

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 given on when to use this tool over alternatives such as get_pull_request_changes or get_pull_request_checks. The description lacks context on when this tool is appropriate.

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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