Bring Ci Cd
to Google ADK
Learn how to connect Dagger (Programmable CI) to Google ADK and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Dagger (Programmable CI) MCP Server?
Connect to the Dagger Engine to orchestrate your delivery pipelines using a powerful, programmable GraphQL API. This server allows your AI agent to interact directly with Dagger's Directed Acyclic Graph (DAG) of operations.
What you can do
- Container Orchestration — Initialize scratch containers, pull images, and manage OCI-compatible states.
- GraphQL Workflows — Execute raw GraphQL queries to compose complex build and test logic dynamically.
- Source Control — Query Git repositories and host environments to pull source code into your pipelines.
- Resource Management — Handle secrets securely, manage persistent cache volumes, and fetch remote files via HTTP.
- Module Inspection — Query the current module state and engine version to ensure environment consistency.
How it works
- Ensure a Dagger Engine is running in your environment.
- Provide the session port and token generated by the Dagger CLI.
- Start building and deploying through natural language commands.
Who is this for?
- DevOps Engineers — Automate pipeline debugging and execution without leaving the chat interface.
- Software Developers — Run builds, tests, and container operations directly from the code editor.
- SREs — Inspect engine states and orchestrate infrastructure tasks using programmable CI logic.
Built-in capabilities (10)
You can chain fields to create a Directed Acyclic Graph (DAG) of operations. Execute a raw GraphQL query against the Dagger engine
Constructs a cache volume
Creates a scratch container and returns its ID
Queries the current module
Creates an empty directory and returns its ID
Queries a Git repository
Queries the host environment
Returns a file from a URL
g., env://VAR_NAME, file://PATH, cmd://COMMAND). Creates a new secret
Get the Dagger Engine version
Why Google ADK?
Google ADK natively supports Dagger (Programmable CI) as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
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Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
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Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Dagger (Programmable CI)
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Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
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Seamless integration with Google Cloud services means you can combine Dagger (Programmable CI) tools with BigQuery, Vertex AI, and Cloud Functions
Dagger (Programmable CI) in Google ADK
Dagger (Programmable CI) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Dagger (Programmable CI) to Google ADK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Dagger (Programmable CI) in Google ADK
The Dagger (Programmable CI) MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 10 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Google ADK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Dagger (Programmable CI) for Google ADK
Every tool call from Google ADK to the Dagger (Programmable CI) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I run a specific build command using Dagger?
You can use the execute_graphql_query tool 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 tool 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 tool 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.
How does Google ADK connect to MCP servers?
Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
Can ADK agents use multiple MCP servers?
Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
Which Gemini models work best with MCP tools?
Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.
McpToolset not found
Update: pip install --upgrade google-adk
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