CI/CD Pipeline Duration Analyzer Connector for AI agents.
4 live capabilities
Speed up your deployment workflows by identifying build bottlenecks and parallelization gaps.
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Why people use CI/CD Pipeline Duration Analyzer
CI/CD Pipeline Duration Analyzer for identifying build bottlenecks
This Connector lets your agent do the heavy lifting. You can just ask it to analyze the execution data and point out the exact stages that are dragging things down. Instead of manual log diving, you get a clear breakdown of what's slow and a prioritized list of what to fix first.
What Vinkius changes
You get a prioritized list of the fastest ways to speed up your builds.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Identifying a mystery slow build
A developer notices the nightly build is taking 40 minutes.
- Real-world use case 02
Planning a pipeline refactor
A platform engineer wants to know if moving to a new runner will help.
- Real-world use case 03
Finding missed parallelization
An SRE wants to know if they can run unit tests and builds at the same time.
Complete set · 4capabilities
The complete CI/CD Pipeline Duration Analyzer capability set.
These are the exact actions your AI can choose when you ask it to work with CI/CD Pipeline Duration Analyzer.
01—04
4 capabilities in this set.
Part of 4 available through CI/CD Pipeline Duration Analyzer.
- 01 Capability
Find parallelization opportunities
Scans your pipeline to find tasks that have no dependencies and can be run at the same time.
- 02 Capability
Get stage impact breakdown
Shows you a list of every stage in your run ranked by how much time they actually take.
- 03 Capability
Estimate optimization gains
Predicts exactly how many minutes you'll save by fixing a specific cache or removing a dependency.
- 04 Capability
Compute execution efficiency
Compares the critical path to the total wall-clock time to see how much of your wait time is wasted.
Set up in minutes
One URL. Then ask CI/CD Pipeline Duration Analyzer to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use CI/CD Pipeline Duration Analyzer from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_LWblQJi98h7HrgOe12o1ytVDei1EX3ex4rUVQzUF/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it CI/CD Pipeline Duration Analyzer, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable CI/CD Pipeline Duration Analyzer for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_LWblQJi98h7HrgOe12o1ytVDei1EX3ex4rUVQzUF/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the CI/CD Pipeline Duration Analyzer URL.
- Step 03
Save and start
Save the connection and enable CI/CD Pipeline Duration Analyzer in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"cicd-pipeline-duration-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_LWblQJi98h7HrgOe12o1ytVDei1EX3ex4rUVQzUF/mcp"
}
}
} - Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using CI/CD Pipeline Duration Analyzer
Open Agent mode in chat and ask: "Using CI/CD Pipeline Duration Analyzer, help me...". 4 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"cicd-pipeline-duration-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_LWblQJi98h7HrgOe12o1ytVDei1EX3ex4rUVQzUF/mcp"
}
}
} - Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using CI/CD Pipeline Duration Analyzer
Ask Copilot: "Using CI/CD Pipeline Duration Analyzer, help me...". 4 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"cicd-pipeline-duration-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_LWblQJi98h7HrgOe12o1ytVDei1EX3ex4rUVQzUF/mcp"
}
}
} - Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using CI/CD Pipeline Duration Analyzer
Open Cascade and ask: "Using CI/CD Pipeline Duration Analyzer, help me...". 4 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"cicd-pipeline-duration-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_LWblQJi98h7HrgOe12o1ytVDei1EX3ex4rUVQzUF/mcp"
}
}
} - Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using CI/CD Pipeline Duration Analyzer
Ask Cline: "Using CI/CD Pipeline Duration Analyzer, help me...". 4 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add cicd-pipeline-duration-analyzer --transport http "https://edge.vinkius.com/vk_preview_LWblQJi98h7HrgOe12o1ytVDei1EX3ex4rUVQzUF/mcp" - Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using CI/CD Pipeline Duration Analyzer
Ask Claude: "Using CI/CD Pipeline Duration Analyzer, show me...". 4 tools are ready
Where the request belongs
Work CI/CD Pipeline Duration Analyzer can move forward.
This is for the DevOps engineer who's tired of watching "building..." spinners for 30 minutes without knowing why. It's for the person responsible for keeping the deployment pipeline fast enough to keep the dev team happy.
DevOps Engineer
Finding out why the production build is lagging on a Tuesday morning.
SRE
Identifying infrastructure bottlenecks that are slowing down the CI/CD cycle.
Platform Engineer
Designing faster deployment paths for hundreds of microservices.
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Bring your own AI
Change the model, client or framework. Keep CI/CD Pipeline Duration Analyzer connected.
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Claude -
ChatGPT -
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Windsurf -
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Before you connect
Questions about CI/CD Pipeline Duration Analyzer.
The practical details behind the request, access and result.
What does the CI/CD Pipeline Duration Analyzer do?
It analyzes your pipeline's execution data to find exactly where your builds are slowing down and identifies ways to make them faster.
How can I use this to speed up my builds?
You can ask your agent to find tasks that can run at the same time or to show you which stages are taking up the most time so you know what to fix first.
Can it tell me which part of my pipeline is the slowest?
Yes, it provides a percentage breakdown of every stage in your run, making it easy to see which specific jobs are the primary bottlenecks.
How does it find ways to run tasks in parallel?
It scans your pipeline metadata to find tasks that don't have dependencies on each other, showing you where you can run things concurrently.
Can it predict how much time I'll save by fixing a cache?
Yes, it can project the estimated time savings for specific optimizations like cache improvements or removing unnecessary dependencies.
Do I need to provide my own logs for this?
You just need to connect your pipeline's execution metadata to the Connector, and your agent can handle the analysis from there.
Is this useful for optimizing my deployment workflow?
Absolutely. It helps you move from guessing why deployments are slow to having a clear, data-driven plan for optimization.
How can I identify which stages are slowing down my pipeline?
You can use the get_stage_impact_breakdown capability to see a list of all stages and the percentage of total runtime each one consumes.
What is the efficiency ratio?
The efficiency ratio, calculated via compute_execution_efficiency, compares the critical path duration to the total wall-clock time. A value closer to 1 indicates a highly optimized pipeline.
Can I simulate future improvements?
Yes, use estimate_optimization_gains to model how changes like 'cache_improvement' or 'dependency_removal' would impact your total duration.
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