CI/CD Pipeline Duration Analyzer

CI/CD Pipeline Duration Analyzer MCP Connector for Claude

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Analyze CI/CD pipeline run data to identify bottlenecks, critical paths, and parallelization opportunities.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides deep analytical insights into your CI/CD pipeline execution metadata. By analyzing temporal overlaps and dependency chains, it helps you understand the efficiency gap between wall-clock time and critical path duration. Use compute_execution_efficiency to compare runtime segments, get_stage_impact_breakdown to find heavy stages, find_parallelization_opportunities to detect sequential tasks that could run concurrently, and estimate_optimization_gains to project savings from cache improvements or dependency removal.

pipelineoptimizationbottleneckautomationmetrics

4 tools expose this connector's capabilities to your AI agent.

estimate_optimization_gains

Estimates the potential time savings from different optimization strategies

get_stage_impact_breakdown

Returns stage breakdown by duration and percentage of total time

find_parallelization_opportunities

Finds stages that could be run concurrently

compute_execution_efficiency

Computes execution efficiency by comparing critical path to wall-clock time

See how to talk to your AI agent using CI/CD Pipeline Duration Analyzer.

How efficient is my latest pipeline run?

The efficiency ratio for the most recent run is 0.75, meaning your critical path takes 75% of the total wall-clock time.

Which stages are taking up most of my pipeline time?

The 'Build' stage is consuming 45% of the total duration, followed by 'Integration Tests' at 30%.

Are there any stages that could be run in parallel?

Yes, the 'Lint' and 'Unit Tests' stages are running sequentially but have no dependency relationship; moving them to run concurrently could save 120 seconds.

You can use the `get_stage_impact_breakdown` tool to see a list of all stages and the percentage of total runtime each one consumes.

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