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Analyze event logs locally with process mining, conformance checks, and OCEL support.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "pm4py-mcp" yet — see the docs or source repo.
Use pm4py-mcp to analyze this event log file, discover the actual execution process, and summarize key paths, bottlenecks, and common variants.
A process model summary with analysis of main paths, exception branches, and process bottlenecks.
Use pm4py-mcp to run conformance checking between this event log and the given process model, then identify deviations, their frequency, and possible causes.
A conformance analysis including deviation points, share of affected cases, and improvement suggestions.
Use pm4py-mcp to analyze this OCEL 2.0 dataset, identify interactions among orders, items, and shipments, and summarize key process patterns.
A summary of inter-object relationships, core interaction flows, and anomaly patterns in multi-object processes.
Delegate summarization, classification, extraction, and drafting tasks to a local LLM.
Build, debug, and manage software tasks with natural language across LLMs.
Analyze disk images with AI through MCP for fast forensic investigation.
Connect to and operate MCP servers from the command line.
Control agent workflows with stateful primitives and persisted execution facts.
Run prompt and RAG evaluations through MCP clients with hosted backend execution.