Dagger (Programmable CI) Connector for AI agents.
10 live capabilities
Run and debug programmable CI pipelines through your AI agent.
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Why people use Dagger (Programmable CI)
Dagger for Programmable CI Pipeline Debugging
With this Connector, you can just tell your agent what you want to build. It queries the engine, manages the DAG, and handles the container states. You get a working build without the manual overhead of tracking every intermediate state.
What Vinkius changes
It gives your agent a direct line to execute programmable CI pipelines.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Debugging a failing build
A developer asks the agent to check the current module state and run a specific GraphQL query to see why a container step failed.
- Real-world use case 02
Dynamic CI generation
A DevOps engineer tells the agent to pull a repo, create a directory, and fetch a remote config file to build a custom image.
- Real-world use case 03
Secure secret management
An SRE asks the agent to create a secret from an environment variable and then run a build that requires that specific credential.
Complete set · 10capabilities
The complete Dagger (Programmable CI) capability set.
These are the exact actions your AI can choose when you ask it to work with Dagger (Programmable CI).
01—04
4 capabilities in this set.
Part of 10 available through Dagger (Programmable CI).
- 01 Capability
Execute graphql query
Run raw GraphQL queries to chain fields into a Directed Acyclic Graph of operations. This lets your agent build complex logic dynamically.
- 02 Capability
Query cache volume
Create a cache volume to persist data between different build steps. It helps avoid redundant work in your pipeline.
- 03 Capability
Query container
Initialize a new scratch container and get its unique state ID. Use this to start a clean environment for your tasks.
- 04 Capability
Query current module
Check the current module state to ensure the environment is consistent. This helps your agent verify the setup before running commands.
05—07
3 capabilities in this set.
Part of 10 available through Dagger (Programmable CI).
- 05 Capability
Query directory
Create a new empty directory and retrieve its ID for use in your pipeline. This is useful for organizing files during a build.
- 06 Capability
Query host
Query the host environment to get information about the underlying system. Use this to check your local or remote machine status.
- 07 Capability
Query http
Fetch a file from a URL to include it in your build process. This lets your agent grab remote configs or assets easily.
08—10
3 capabilities in this set.
Part of 10 available through Dagger (Programmable CI).
- 08 Capability
Query secret
Create a new secret using environment variables, files, or commands. It keeps your credentials safe while your agent runs builds.
- 09 Capability
Query version
Get the current Dagger Engine version to verify your setup. Use this to make sure your environment matches your requirements.
- 10 Capability
Query git
Query a specific Git repository to pull source code into your workflow. Your agent can fetch the latest code automatically.
Set up in minutes
One URL. Then ask Dagger (Programmable CI) to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Dagger (Programmable CI) 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_jU749naeDKubVrRR38BTiJPB8XzxtT6YXppJtFAW/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 Dagger (Programmable CI), and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Dagger (Programmable CI) for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_jU749naeDKubVrRR38BTiJPB8XzxtT6YXppJtFAW/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 Dagger (Programmable CI) URL.
- Step 03
Save and start
Save the connection and enable Dagger (Programmable CI) in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"dagger-programmable-ci": {
"url": "https://edge.vinkius.com/vk_preview_jU749naeDKubVrRR38BTiJPB8XzxtT6YXppJtFAW/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 Dagger (Programmable CI)
Open Agent mode in chat and ask: "Using Dagger (Programmable CI), help me...". 10 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"dagger-programmable-ci": {
"url": "https://edge.vinkius.com/vk_preview_jU749naeDKubVrRR38BTiJPB8XzxtT6YXppJtFAW/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 Dagger (Programmable CI)
Ask Copilot: "Using Dagger (Programmable CI), help me...". 10 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"dagger-programmable-ci": {
"url": "https://edge.vinkius.com/vk_preview_jU749naeDKubVrRR38BTiJPB8XzxtT6YXppJtFAW/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 Dagger (Programmable CI)
Open Cascade and ask: "Using Dagger (Programmable CI), help me...". 10 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"dagger-programmable-ci": {
"url": "https://edge.vinkius.com/vk_preview_jU749naeDKubVrRR38BTiJPB8XzxtT6YXppJtFAW/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 Dagger (Programmable CI)
Ask Cline: "Using Dagger (Programmable CI), help me...". 10 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add dagger-programmable-ci --transport http "https://edge.vinkius.com/vk_preview_jU749naeDKubVrRR38BTiJPB8XzxtT6YXppJtFAW/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 Dagger (Programmable CI)
Ask Claude: "Using Dagger (Programmable CI), show me...". 10 tools are ready
Where the request belongs
Work Dagger can move forward.
This is for the DevOps engineer tired of debugging broken YAML files at 2am, the developer who wants to run container tests without leaving their editor, and the SRE managing complex infrastructure tasks.
DevOps Engineer
They use this to debug failing pipeline steps and run complex build logic via chat instead of manual CLI commands.
Software Developer
They trigger builds, run container tests, and pull code into their local environment using natural language prompts.
SRE
They inspect engine states and orchestrate infrastructure tasks using programmable CI logic to ensure environment consistency.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsSemaphore
Automate CI/CD workflows, manage pipelines, and monitor build jobs directly from your AI agent.
Woodpecker CI
Manage your Woodpecker CI instance. control pipelines, monitor agents, and configure repositories directly from your AI agent.
Drone CI
Automate your CI/CD workflows with Drone CI—manage repositories, monitor builds, and handle secrets directly from your AI agent.
Travis CI
Manage CI/CD pipelines, trigger custom builds, and oversee repository testing health securely via your AI agent.
Harness
Automate CI/CD and DevOps workflows via Harness. manage pipelines, executions, and secrets directly from any AI agent.
Codefresh
Manage CI/CD and GitOps via Codefresh. track pipelines, trigger builds, and monitor delivery clusters directly from any AI agent.
Bring your own AI
Change the model, client or framework. Keep Dagger connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Dagger.
The practical details behind the request, access and result.
How does Dagger MCP help with CI/CD?
It gives your AI agent the ability to run and manage programmable CI pipelines. Instead of writing long scripts, your agent can execute complex build logic and manage container states directly.
Can I use Dagger MCP to manage secrets?
Yes, your agent can create and manage secrets from environment variables, files, or commands. This keeps your sensitive credentials out of the chat history while still allowing the build to run.
Does Dagger MCP work with my existing Dagger Engine?
Yes, it connects directly to your running Dagger Engine. You just need to provide the session port and token generated by your Dagger CLI.
How does Dagger MCP handle container states?
It allows your agent to initialize scratch containers and retrieve unique state IDs. This makes it easy to chain multiple operations together in a specific order.
Can Dagger MCP pull code from different repos?
Yes, your agent can query specific Git repositories to pull source code into your pipeline automatically, making it easy to build projects with multiple dependencies.
Is Dagger MCP good for debugging complex pipelines?
It is excellent for debugging because it allows your agent to inspect the current module state and run specific GraphQL queries to isolate exactly where a build step is failing.
How do I run a specific build command using Dagger?
You can use the execute_graphql_query capability to send a raw GraphQL query to the Dagger engine, allowing you to chain container operations like from, withExec, and stdout.
Can I access files from my local machine in the pipeline?
Yes, the query_host capability allows you to retrieve the state ID for your host environment, which can then be used to mount local directories into your Dagger containers.
How are secrets handled in this integration?
Use the query_secret capability to load secrets from URIs (like env:// or file://). This returns a secret ID that can be safely passed to other Dagger operations without exposing the plaintext value.
One connection away
Give your agent a direct line to Dagger.
Connect Dagger once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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