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ado-mcp-server

ado-mcp-server

by ms31376
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_pull_request

Read-only

Retrieve pull request details—description, reviewers, votes, and linked work items—to review code changes and track approvals.

Instructions

Details of a pull request: description, reviewers and votes, linked work items.

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": {
      "pull_request_id": "<pull_request_id>"
    },
    "name": "get_pull_request"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectNo
pull_request_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.1/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful return-content context by naming the pull request details exposed, which matters because there is no output schema, but it omits error behavior, permissions, and project scoping.

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 front-loaded sentence with no filler. It efficiently communicates the core resource and the main details returned.

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?

For a simple read-only retrieval tool, the description identifies the returned data and annotations cover safety. However, it leaves gaps around parameter semantics and when to choose this tool over list_pull_requests.

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?

Schema description coverage is 0%, and the description does not explain either parameter. The pull_request_id name is fairly self-explanatory, but the optional project parameter and its default behavior are left undocumented.

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 that the tool returns details of a pull request and enumerates key fields such as description, reviewers/votes, and linked work items. The resource is unambiguous, but it does not explicitly distinguish itself from the sibling list_pull_requests tool.

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?

There is no explicit guidance on when to use this tool versus list_pull_requests or other retrieval tools. Usage is only implied by the tool name and required pull_request_id parameter.

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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