Get logs for a specific pipeline step. Useful for debugging individual step failures or examining step output.
AI agents call get_step_logs to retrieve information from Woodpecker without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves historical log information from a completed or running pipeline step for inspection and debugging purposes. It has no side effects, does not execute code, does not modify data, and does not delete anything. It is a pure read operation that queries and returns log output.
From the tool's definition Tool name 'get_step_logs' and description 'Get logs for a specific pipeline step' indicates retrieval of existing log data with no modification or execution capability.
Documented attack patterns abuse exactly the kind of access get_step_logs gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Woodpecker, and nothing reaches the server without passing your rules. This is the rule we recommend for get_step_logs:
{
"version": "1",
"default": "deny",
"tools": {
"get_step_logs": {}
}
}get_step_logs is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get logs for a specific pipeline step. Useful for debugging individual step failures or examining step output. It is categorised as a Read tool in the Woodpecker MCP Server, which means it retrieves data without modifying state.
Register the Woodpecker MCP server in PolicyLayer and add a rule for get_step_logs: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Woodpecker. Nothing to install.
get_step_logs is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_step_logs rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for get_step_logs. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
get_step_logs is provided by the Woodpecker MCP server (j04n-f/woodpecker-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Woodpecker, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
7 Woodpecker tools catalogued and risk-classified — across an index of 43,000+ MCP servers.