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Azure DevOps MCP Server

Azure DevOps MCP Server

by allanbrunobr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

search_work_items

Search Azure DevOps work items using natural language queries across titles, descriptions, and comments. Find relevant items faster than with WIQL queries.

Instructions

Search work items by text across title, description and comments. Easier than WIQL for natural language queries.

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": {
      "searchText": "<searchText>"
    },
    "name": "search_work_items"
  }
}

Input Schema

NameRequiredDescriptionDefault
searchTextYesText to search for (e.g., "login bug", "payment timeout")
topNoMax results to return (default: 25)
skipNoNumber of results to skip for pagination (default: 0)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
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 of behavioral disclosure. While it mentions the search scope and comparison to WIQL, it doesn't describe important behavioral traits like whether this is a read-only operation, what permissions are required, how results are sorted, or if there are rate limits. For a search tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 extremely concise (two sentences) and front-loaded with the core purpose. Every sentence adds value: the first defines what the tool does, and the second provides important usage guidance. There's zero wasted text or redundancy.

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 (search functionality with 3 parameters), no annotations, and no output schema, the description provides adequate but incomplete context. It covers the purpose and basic usage but lacks behavioral details and output information. For a search tool without annotations or output schema, more context about result format or limitations would be helpful.

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 schema description coverage is 100%, so all parameters are documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain search syntax, ranking, or field weighting). With complete schema coverage, the baseline score of 3 is appropriate as the description doesn't enhance parameter understanding.

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 clearly states the specific verb ('Search') and resource ('work items'), specifying the search scope ('across title, description and comments') and distinguishing it from alternatives ('Easier than WIQL for natural language queries'). This provides a precise purpose that differentiates it from sibling tools like 'list_work_items' or 'query_work_items'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides usage guidance by stating when to use this tool ('Easier than WIQL for natural language queries'), which implicitly suggests it's preferred over WIQL-based tools like 'query_work_items' for text-based searches. This gives clear context for choosing this tool over alternatives.

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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