mcp-server-bitbucket

get_pipeline_logs

Retrieve pipeline execution logs or list available steps for debugging Bitbucket CI/CD workflows. Provide repository slug and pipeline UUID to access detailed run information.

Instructions

Get logs for a pipeline run.

If step_uuid is not provided, returns list of steps to choose from.

Args:
    repo_slug: Repository slug
    pipeline_uuid: Pipeline UUID
    step_uuid: Step UUID (optional, get from steps list first)

Returns:
    Pipeline logs or list of available steps

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": {
      "repo_slug": "<repo_slug>",
      "pipeline_uuid": "<pipeline_uuid>"
    },
    "name": "get_pipeline_logs"
  }
}

Input Schema

Name	Required	Description	Default
`repo_slug`	Yes
`step_uuid`	No
`pipeline_uuid`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Dec 20, 2025

TDQS

A4/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the tool's conditional behavior (returns logs or steps list based on step_uuid), which is helpful. However, it lacks details on permissions, rate limits, error handling, or output format, leaving gaps for a mutation-like read 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 well-structured and front-loaded with the core purpose, followed by clear sections for arguments and returns. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 no annotations and no output schema, the description does a decent job but has gaps. It explains the tool's conditional behavior and parameters well, but doesn't cover return formats, error cases, or system constraints. For a tool with 3 parameters and conditional outputs, more completeness would be beneficial.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's role: repo_slug and pipeline_uuid as required identifiers, and step_uuid as optional with guidance to 'get from steps list first.' This fully compensates for the schema's lack of descriptions.

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 tool's purpose: 'Get logs for a pipeline run.' It specifies the resource (pipeline logs) and the action (get). However, it doesn't explicitly differentiate from sibling tools like 'get_pipeline' or 'list_pipelines', which reduces it from a perfect score.

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

Usage Guidelines4/5

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

The description provides clear usage guidance: 'If step_uuid is not provided, returns list of steps to choose from.' This explains when to use it with or without the optional parameter. It doesn't mention alternatives or exclusions, but the context is well-defined.

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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