GitLab MCP Server

get_job_log

Retrieve the trace log of a GitLab job using its project path and job ID.

Instructions

Get the log/trace output of a specific job.

Args: project_path: Full path of the project (e.g., 'group/project') job_id: The ID of the job

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": {
      "project_path": "<project_path>",
      "job_id": "<job_id>"
    },
    "name": "get_job_log"
  }
}

Input Schema

Name	Required	Description	Default
`job_id`	Yes
`project_path`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 6, 2026

TDQS

A4.3/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes the core function but does not disclose additional behavioral traits such as authentication requirements, rate limits, or output format details. It does not add significant context beyond the basic 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, with a single line for purpose and two lines for parameter descriptions. It is front-loaded with the core action, and every sentence earns its place.

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

Completeness5/5

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

Given the low complexity (two required parameters) and the presence of an output schema, the description is complete. It covers the purpose and parameter details sufficiently for an agent to use the tool correctly.

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

Parameters4/5

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

Schema description coverage is 0%, but the description provides clear, human-readable definitions for both parameters (project_path as 'Full path of the project' with example, job_id as 'The ID of the job'). This adds meaningful value beyond the schema's type-only information.

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 tool retrieves log/trace output for a specific job, using a specific verb 'Get' and resource 'log/trace output of a specific job'. It distinguishes itself from sibling tools which focus on files, issues, merge requests, etc.

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 implies usage when you need log output for a job, but does not provide explicit guidance on when not to use it or mention alternatives. However, for a straightforward retrieval tool, the context is clear.

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