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Git Dora

by Saikat MondalUpdated May 4, 2026

Computes DORA metrics (deployment frequency, lead time for changes, change failure rate, time to restore service), bus factor, and code churn from any Git repository. Software engineering teams and managers use it to evaluate repo health, team performance, and maintenance risks. Provides data for identifying bottlenecks in CI/CD pipelines and contributor dependencies without paid tools.

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Overview

Git Dora is an MCP server that analyzes Git repositories to extract DORA metrics, bus factor, and code churn. It processes commit history, pull requests, and deployment data to quantify engineering performance and repo risks, serving as a free alternative to tools like LinearB and Swarmia.

Key Capabilities

  • DORA Metrics: Calculates deployment frequency, lead time for changes, change failure rate, and time to restore service based on Git commit and tag data.
  • Bus Factor: Determines the minimum number of developers needed to maintain the repository by analyzing contributor commit patterns.
  • Code Churn: Measures lines of code added, modified, or deleted over time, highlighting unstable areas.

These functions query the repo directly via Git, requiring only a repository URL or clone access.

Use Cases

  1. Performance Benchmarking: An engineering manager inputs a team's GitHub repo URL to compute DORA metrics, comparing deployment frequency against elite performer benchmarks to set improvement goals.
  2. Risk Assessment: Before a project handoff, calculate bus factor on a repo to identify single points of failure among contributors.
  3. Code Quality Monitoring: Track code churn in a monorepo to detect high-churn modules, prioritizing refactoring efforts.
  4. CI/CD Optimization: Analyze lead time for changes across branches to diagnose delays in merge-to-deploy pipelines.

Who This Is For

Engineering managers tracking DORA metrics for DevOps reports, developers auditing repo health, and open-source maintainers evaluating contributor risks. Ideal for teams using GitHub, GitLab, or Bitbucket without budgets for commercial analytics platforms.