io.github.CloudCorpRecords/buildtime

Official registry Other

Build bottleneck profiler: slowest steps, run trend, and cache correlation across CI runs.

What can you do with io.github.CloudCorpRecords/buildtime?

  • analyze_build_times — Profile build bottlenecks across

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

NPM package @reneturcios/buildtime
Claude Code
claude mcp add buildtime -- npx -y @reneturcios/buildtime@0.1.0 mcp
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "buildtime": {
            "command": "npx",
            "args": [
                "-y",
                "@reneturcios/buildtime@0.1.0",
                "mcp"
            ]
        }
    }
}
OCI package ghcr.io/cloudcorprecords/buildtime:0.1.0
Claude Code
claude mcp add buildtime -- docker run -i --rm ghcr.io/cloudcorprecords/buildtime:0.1.0 mcp
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "buildtime": {
            "command": "docker",
            "args": [
                "run",
                "-i",
                "--rm",
                "ghcr.io/cloudcorprecords/buildtime:0.1.0",
                "mcp"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. buildtime
  2. CLI
  3. MCP server
  4. Docker
  5. Development
  6. License

buildtime

Your builds keep getting slower, but which step is to blame? buildtime profiles a set of CI runs — per-step durations and, where known, cache hits — and answers with the numbers that point at the bottleneck:

  • Per-step statistics — for every distinct step name: how many runs contained it, its total, average, and maximum duration, and its share of the grand total, sorted slowest first (ties by name)
  • Slowest step — the first entry in that ranking
  • Trend — the runs, in the order supplied, split into a first half and a second half (the middle run of an odd count belongs to the first half), with each half's average run total and the percentage delta between them; null with fewer than two runs, and the delta itself is null when the first half averages zero
  • Cache correlation — a run counts as "with cache" when at least one of its steps reports a cache hit; buildtime reports both group sizes and each group's average run total (null for an empty group, never zero-filled)
  • Flagged slowest — when you pass a slow threshold, the steps whose average duration meets or exceeds it, in slowest-first order

All floats are rounded to four decimal places. The computation is pure and local: no network, no configuration, no files read beyond the runs you pass in. Invalid input — a missing run, a step without a duration, a negative duration — is rejected with an error naming the offending path, and no partial profile is produced.

CLI

npx @reneturcios/buildtime analyze --runs runs.json
npx @reneturcios/buildtime --version

runs.json contains the full arguments object:

{
  "runs": [
    {
      "run_id": "run-101",
      "conclusion": "success",
      "steps": [
        { "name": "compile", "duration_seconds": 42.5, "cache_hit": true },
        { "name": "test", "duration_seconds": 87 }
      ]
    }
  ],
  "slow_threshold_seconds": 60
}

conclusion and cache_hit are optional per run / per step, and slow_threshold_seconds is optional overall. The profile is printed as JSON.

Exit codes: 0 on success, 1 on a runtime error (including an unreadable or invalid runs file, or invalid input), 2 on a usage error.

MCP server

npx -y @reneturcios/buildtime mcp

MCP client config:

{
  "mcpServers": {
    "buildtime": {
      "command": "npx",
      "args": ["-y", "@reneturcios/buildtime", "mcp"]
    }
  }
}
Tools
  • analyze_build_times — Profile build bottlenecks across CI runs.

    • runs (array, required, at least one) — runs as {run_id, conclusion?, steps} objects, where each step is {name, duration_seconds, cache_hit?}
    • slow_threshold_seconds (number, optional, >= 0) — flag steps whose average duration meets this threshold

    Returns {run_count, grand_total_seconds, step_stats, slowest_step, trend, cache, flagged_slowest}.

Docker

docker run -i ghcr.io/cloudcorprecords/buildtime
docker run --rm -v "$PWD:/w" ghcr.io/cloudcorprecords/buildtime analyze --runs /w/runs.json

Development

npm install
npm run build   # tsc -> dist/
npm test        # tsx --test test/*.test.ts (pure local, no network)
npm run dev     # run the CLI from source

License

MIT — Copyright (c) 2026 Rene Turcios

Frequently asked questions

What is io.github.CloudCorpRecords/buildtime?

Build bottleneck profiler: slowest steps, run trend, and cache correlation across CI runs.

How do I install io.github.CloudCorpRecords/buildtime?

It runs on your machine. In Claude Code: claude mcp add buildtime -- npx -y @reneturcios/buildtime@0.1.0 mcp. For other clients, paste the JSON configuration from this page into their MCP settings.

Does io.github.CloudCorpRecords/buildtime need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is io.github.CloudCorpRecords/buildtime open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains io.github.CloudCorpRecords/buildtime?

It is published by CloudCorpRecords. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.