Skip to main content
Glama
Azure DevOps MCP Server
by billg118

search_code

Find code across Azure DevOps project repositories using text queries and filters for repository, branch, path, and code element to locate matching files and snippets.

Instructions

Search for code across repositories in a project

Input Schema

NameRequiredDescriptionDefault
topYesNumber of results to return (default: 100, max: 1000)
skipYesNumber of results to skip for pagination (default: 0)
filtersNoOptional filters to narrow search results
projectIdNoThe ID or name of the project to search in (Default: no default project). If not provided, the default project will be used.
searchTextYesThe text to search for
includeContentYesWhether to include full file content in results (default: true)
includeSnippetYesWhether to include code snippets in results (default: true)
organizationIdNoThe ID or name of the organization (Default: example-org)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.54

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden, and it discloses almost nothing. It does not state whether matching is literal or regex, case sensitivity, result ranking, pagination semantics, permission requirements, or what happens when projectId/organizationId are omitted beyond what the schema hints at.

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?

A single front-loaded sentence with no filler or redundancy. Every word describes the tool's scope; the terseness is a coverage problem rather than a conciseness problem.

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?

For a tool with 8 parameters, a nested filters object, 5 required fields, no annotations, and no output schema, one sentence is not sufficient. Missing are search semantics, default-project behavior, result shape, and pagination behavior, all of which an agent needs to invoke it correctly.

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%, with every parameter including the nested filters object documented in the schema, so the baseline is 3. The description adds no meaning beyond the schema — it does not explain how filters combine, whether searchText is literal or pattern-based, or how projectId and organizationId interact.

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 names a concrete verb (Search) and resource (code) with an explicit scope ('across repositories in a project'), so an agent can distinguish it from search_wiki and search_work_items. It stops short of naming a sibling or stating how it differs from get_file_content or get_repository_tree, which keeps it below a 5.

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 when-to-use guidance, no when-not-to-use exclusions, and no mention of alternatives. An agent must infer from the name alone that this is the full-text/structural code lookup rather than file-tree traversal or single-file retrieval.

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