Compatible with every major AI agent and IDE
Execute graphql query on Dagger (Programmable CI)
You can chain fields to create a Directed Acyclic Graph (DAG) of operations. Execute a raw GraphQL query against the Dagger engine
Query cache volume on Dagger (Programmable CI)
Constructs a cache volume
Query container on Dagger (Programmable CI)
Creates a scratch container and returns its ID
Query current module on Dagger (Programmable CI)
Queries the current module
Query directory on Dagger (Programmable CI)
Creates an empty directory and returns its ID
Query git on Dagger (Programmable CI)
Queries a Git repository
Query host on Dagger (Programmable CI)
Queries the host environment
Query http on Dagger (Programmable CI)
Returns a file from a URL
Query secret on Dagger (Programmable CI)
g., env://VAR_NAME, file://PATH, cmd://COMMAND). Creates a new secret
Query version on Dagger (Programmable CI)
Get the Dagger Engine version
How Vinkius protects your data
Is there a risk of the AI "going crazy" and deleting important company data?
No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.
Can I set different limits for each virtual assistant on my team?
Absolutely. You have full control in our command center. You can create an AI agent that only "reads" data so the support team can answer questions, and another superpowered agent that can "edit" and "create" information exclusively for your operations team. Each AI gets exactly the level of access you allow.
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.
Does the AI train on my tools or API data?
No. Vinkius enforces a strict Zero-Retention policy. Your data simply passes through our secure servers to complete the requested action and is instantly forgotten. Nothing you do here is ever stored, logged, or used to train any artificial intelligence.
Dagger (Programmable CI) Capabilities for AI Assistants
Use Dagger (Programmable CI) with any AI agent framework to process, analyze, and mutate data securely via the Model Context Protocol.
Claude Code Integration for ci cd
Integrate Dagger (Programmable CI) to access native ci cd capabilities. This allows LLMs to perform secure, deterministic execution of loved by devs tasks without hard-coded API scripts.
LLM Orchestration for container orchestration
The Dagger (Programmable CI) MCP translates LLM intent into specific container orchestration actions. Agents like Cursor use this to interface securely with your loved by devs infrastructure.
Dagger (Programmable CI). Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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