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Azure DevOps MCP Server

Azure DevOps MCP Server

by jafarimohammad
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Run pipeline

run_pipeline

Queue a new pipeline run by its numeric ID. Optionally specify project and branch to override defaults.

Instructions

Queue a new run of a pipeline by its numeric id. Use run_pipeline_by_name if you only know the name.

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": {
      "pipelineId": "<pipelineId>"
    },
    "name": "run_pipeline"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectNoAzure DevOps project name or id. Defaults to AZDO_PROJECT if set.
pipelineIdYesPipeline id (from list_pipelines).
branchNoBranch to run against, without refs/heads/. Defaults to the pipeline default.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior2/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It states 'Queue a new run' implying a mutation, but lacks details on permissions, idempotency, side effects (e.g., triggering a build immediately), or return value. The description is too minimal for a create 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 extremely concise at two sentences, with no wasted words. The first sentence states the primary action, and the second provides a usage alternative. This is efficient and front-loaded.

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?

Given the tool is a mutation (queue action) with 3 parameters, no output schema, and no annotations, the description should cover return value, error behavior, and potential prerequisites. It does not mention what the tool returns (e.g., a run ID) or any conditions that might cause failure. The completeness is inadequate.

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 already documents all three parameters with 100% coverage. The description adds no additional parameter-level details beyond noting that the pipeline is identified by numeric id, which aligns with the 'pipelineId' parameter. The mention of 'run_pipeline_by_name' is about tool selection, not parameter semantics. Baseline of 3 is appropriate.

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 action ('Queue a new run') and the resource ('a pipeline by its numeric id'), and explicitly distinguishes from the sibling tool 'run_pipeline_by_name', which is used when only the name is known. This provides specific verb+resource identification and differentiation.

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 provides explicit guidance on when to use this tool (when you have the numeric id) and when to use the alternative ('run_pipeline_by_name' if you only know the name). This directly helps the agent choose the correct tool.

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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