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Glama
Azure DevOps MCP Server
by billg118

get_all_repositories_tree

Generates a hierarchical tree view of files and directories across multiple Azure DevOps repositories in a project from their default branches, with optional depth and pattern filters.

Instructions

Displays a hierarchical tree view of files and directories across multiple Azure DevOps repositories within a project, based on their default branches

Input Schema

NameRequiredDescriptionDefault
depthYesMaximum depth to traverse within each repository (0 = unlimited)
patternNoFile pattern (wildcard characters allowed) to filter files by within each repository
projectIdNoThe ID or name of the project (Default: no default project)
organizationIdNoThe ID or name of the Azure DevOps organization (Default: example-org)
repositoryPatternNoRepository name pattern (wildcard characters allowed) to filter which repositories are included

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.54

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it usefully discloses that traversal is based on each repository's default branch, which is real behavioral context an agent could not otherwise know. It says nothing about whether non-default branches are reachable, output shape, size limits, or performance when many repos match.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single well-formed sentence with the action and scope front-loaded and no filler. It leaves room for a sibling contrast that a fifth scoring level would require, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema and no annotations, but the description establishes the key mental model (a tree rooted at each repo's default branch) plus the schema fully covers all five parameters. Given a simple read-only listing tool, what remains missing — return format and cost at scale — is minor.

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 coverage is 100%, so depth, pattern, projectId, organizationId, and repositoryPattern are all documented in the schema, including the 0 = unlimited convention and wildcard support. The description adds only the 'default branches' scoping fact and no parameter-level meaning beyond the schema, so baseline 3 applies.

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 specific verb ('Displays') and resource ('hierarchical tree view of files and directories') and qualifies the scope as 'across multiple Azure DevOps repositories within a project'. This distinguishes it in substance from the single-repository sibling get_repository_tree, though that sibling is never named, so an agent must infer the boundary.

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

Usage Guidelines3/5

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

'Across multiple repositories' implies the cross-repo use case, but there is no explicit guidance on when to pick this over get_repository_tree or list_repositories, and no mention of prerequisites or cost of spanning many repos. Usage is inferable rather than stated.

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