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Azure DevOps MCP Server with PAT Authentication

Azure DevOps MCP Server with PAT Authentication

by ennuiii
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

core_get_identity_ids

Retrieve Azure DevOps identity IDs by providing a search filter such as unique name, display name, or email, using PAT authentication.

Instructions

Retrieve Azure DevOps identity IDs for a provided search filter.

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": {
      "searchFilter": "<searchFilter>"
    },
    "name": "core_get_identity_ids"
  }
}

Input Schema

NameRequiredDescriptionDefault
searchFilterYesSearch filter (unique namme, display name, email) to retrieve identity IDs for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
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 tool retrieves IDs but doesn't disclose behavioral traits like authentication requirements, rate limits, pagination, error handling, or what happens if no matches are found. This leaves significant gaps for a retrieval operation.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to understand quickly.

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?

Given the tool's moderate complexity (retrieval with a filter), no annotations, and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose but lacks details on behavior, usage context, and output format, which are important for effective tool invocation.

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 schema already documents the single parameter 'searchFilter' with its description. The description adds no additional meaning beyond what the schema provides, such as examples of valid filters or search syntax. Baseline 3 is appropriate when schema does the heavy lifting.

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 ('Retrieve') and resource ('Azure DevOps identity IDs') with a specific scope ('for a provided search filter'). It distinguishes itself from sibling tools that handle builds, releases, repositories, etc., but doesn't explicitly differentiate from potential identity-related siblings (none are listed).

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. The description mentions a search filter but doesn't specify scenarios, prerequisites, or exclusions. Sibling tools include various retrieval functions, but no explicit comparison is made.

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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