Skip to main content
Glama

get_step_logs

Retrieve detailed logs for a specific build step in Codemagic CI/CD pipelines to debug and analyze step execution.

Instructions

Get the raw logs for a specific build step.

Use get_build_logs first to see all step IDs, then call this to drill into a specific step.

Args: build_id: The Codemagic build ID. step_id: The step ID (from get_build_logs output).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
build_idYes
step_idYes

Implementation Reference

  • The MCP tool handler for 'get_step_logs'. It accepts build_id and step_id and delegates to the CodemagicClient.
    @mcp.tool()
    async def get_step_logs(build_id: str, step_id: str) -> Any:
        """Get the raw logs for a specific build step.
    
        Use get_build_logs first to see all step IDs, then call this to drill into a specific step.
    
        Args:
            build_id: The Codemagic build ID.
            step_id: The step ID (from get_build_logs output).
        """
        async with CodemagicClient() as client:
            return await client.get_step_logs(build_id, step_id)
  • The actual implementation of the log retrieval logic in the CodemagicClient, which performs the HTTP request to the API.
    async def get_step_logs(self, build_id: str, step_id: str) -> str:
        response = await self._client.get(f"/builds/{build_id}/step/{step_id}")
        response.raise_for_status()
        return response.text
Behavior3/5

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

No annotations provided, so description carries full burden. Adds 'raw' trait (unprocessed logs) and establishes drill-down workflow, but omits safety confirmation (read-only vs mutation), return format details, and error conditions (e.g., invalid step_id behavior) that annotations would typically cover.

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?

Three distinct segments: purpose (sentence 1), workflow guidance (sentence 2), and parameter documentation (Args block). No redundant text; every sentence delivers actionable information. Well front-loaded with verb-first structure.

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?

Given 2 simple parameters and no output schema, description adequately covers invocation workflow and parameter sourcing. Minor gap: lacks description of return value format (string vs JSON vs stream) which would help given absence of output schema.

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?

Schema has 0% description coverage, but description's Args section fully compensates by documenting both parameters: build_id as 'The Codemagic build ID' and crucially noting step_id comes 'from get_build_logs output', providing essential semantic context for the dependency chain.

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?

States specific action ('Get the raw logs') and resource ('specific build step'). Distinguishes from sibling get_build_logs by emphasizing 'raw logs' (detailed content) versus the workflow instruction to use get_build_logs first for IDs, clearly differentiating scope.

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?

Provides explicit sequential guidance ('Use get_build_logs first...then call this') naming the prerequisite sibling tool and explaining the two-step workflow. Clear when-to-use context prevents incorrect standalone invocation.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AgiMaulana/CodemagicMcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server