Skip to main content
Glama
PrefectHQ

prefect-mcp-server

Official
by PrefectHQ

get_flow_run_logs

Retrieve execution logs from a Prefect flow run to view timestamps, log levels, and messages for debugging and monitoring.

Instructions

Get execution logs for a flow run.

Retrieves log entries from the flow run execution, including timestamps, log levels, and messages.

Examples: - Get logs: get_flow_run_logs(flow_run_id="...") - Get more logs: get_flow_run_logs(flow_run_id="...", limit=500)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of log entries to return
flow_run_idYesUUID of the flow run to get logs for
workspace_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
logsYes
errorYes
limitYes
successYes
truncatedYes
flow_run_idYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden for behavioral traits. It does not disclose whether the operation is read-only, any rate limits, or ordering of results. The description only states what is retrieved, lacking deeper behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with a clear purpose statement and examples. However, the two examples are very similar and could be combined. It is front-loaded with the primary action, making it efficient for quick scanning.

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 the tool's simplicity (3 parameters, one required, output schema exists), the description adequately covers the core functionality. It does not mention pagination or default ordering, but the limit parameter addresses page size. For a log retrieval tool, it is reasonably complete.

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?

Schema description coverage is 67% (two of three parameters have descriptions in the schema). The description adds little beyond the schema, only using placeholders in examples. It does not explain the workspace_id parameter's role or format beyond the schema, so it meets the baseline but adds minimal extra value.

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 that the tool retrieves execution logs for a flow run, including specific attributes like timestamps, log levels, and messages. It distinguishes itself from sibling tools like get_task_runs and get_flow_runs by focusing specifically on logs for a flow run.

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

Usage Guidelines3/5

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

The description provides examples of usage but does not give explicit guidance on when to use this tool versus alternatives like get_task_runs for task-level logs. There is no mention of when not to use it or prerequisites, but the examples help imply typical usage.

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/PrefectHQ/prefect-mcp-server'

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