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Monitor, manage, and debug Prefect workflows and resources through AI.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "prefect-mcp-server" yet — see the docs or source repo.
Connect to Prefect and list flow runs that failed or are retrying in the last 24 hours, then summarize the reasons grouped by project.
A list of problematic runs, their projects, current states, and summarized failure reasons for quick inspection.
Inspect the most recent failed run of this Prefect deployment, including task details, logs, and dependencies, and identify the most likely source of the error.
Key failed-task logs, upstream/downstream relationships, and likely root causes to help troubleshoot the issue.
List all current Prefect deployments and their schedule states, identify paused or long-idle deployments, and provide recommendations.
A deployment inventory, schedule states, flagged issues, and suggested actions to keep workflows healthy.
Connect to Prefect to monitor, debug, and manage workflows and deployments.
Build AI agent workflows and automate tasks using MCP-connected services.
Build, debug, and manage software tasks with natural language across LLMs.
Add agentic tools with iterative reasoning and tool use to apps
Review code, chat with repositories, and manage repository operations.
Orchestrate multiple AI agents in real time and monitor tasks and artifacts.