Dagger (Programmable CI) MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 10 tools to Execute Graphql Query, Query Cache Volume, Query Container, and more

Name: Dagger (Programmable CI)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Dagger (Programmable CI) through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

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The Dagger (Programmable CI) MCP Server for OpenAI Agents SDK is a standout in the Loved By Devs category — giving your AI agent 10 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Dagger (Programmable CI) Assistant",
            instructions=(
                "You help users interact with Dagger (Programmable CI). "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Dagger (Programmable CI)"
        )
        print(result.final_output)

asyncio.run(main())

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* 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

About 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.

The OpenAI Agents SDK auto-discovers all 10 tools from Dagger (Programmable CI) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Dagger (Programmable CI), another analyzes results, and a third generates reports, all orchestrated through Vinkius.

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.

The Dagger (Programmable CI) MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 10 Dagger (Programmable CI) tools available for OpenAI Agents SDK

When OpenAI Agents SDK connects to Dagger (Programmable CI) through Vinkius, your AI agent gets direct access to every tool listed below — spanning ci-cd, container-orchestration, pipeline-automation, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

execute

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

Query cache volume on Dagger (Programmable CI)

Constructs a cache volume

query

Query container on Dagger (Programmable CI)

Creates a scratch container and returns its ID

query

Query current module on Dagger (Programmable CI)

Queries the current module

query

Query directory on Dagger (Programmable CI)

Creates an empty directory and returns its ID

query

Query git on Dagger (Programmable CI)

Queries a Git repository

query

Query host on Dagger (Programmable CI)

Queries the host environment

query

Query http on Dagger (Programmable CI)

Returns a file from a URL

query

Query secret on Dagger (Programmable CI)

g., env://VAR_NAME, file://PATH, cmd://COMMAND). Creates a new secret

query

Query version on Dagger (Programmable CI)

Get the Dagger Engine version

Connect Dagger (Programmable CI) to OpenAI Agents SDK via MCP

Follow these steps to wire Dagger (Programmable CI) into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 10 tools from Dagger (Programmable CI)

Why Use OpenAI Agents SDK with the Dagger (Programmable CI) MCP Server

OpenAI Agents SDK provides unique advantages when paired with Dagger (Programmable CI) through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Dagger (Programmable CI) + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Dagger (Programmable CI) MCP Server delivers measurable value.

Automated workflows: build agents that query Dagger (Programmable CI), process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Dagger (Programmable CI), another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Dagger (Programmable CI) tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Dagger (Programmable CI) to resolve tickets, look up records, and update statuses without human intervention

Example Prompts for Dagger (Programmable CI) in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Dagger (Programmable CI) immediately.

"Check the current version of the Dagger engine."

"Initialize a scratch container and return its ID."

"Get the state of the git repository at https://github.com/dagger/dagger."

Troubleshooting Dagger (Programmable CI) MCP Server with OpenAI Agents SDK

Common issues when connecting Dagger (Programmable CI) to OpenAI Agents SDK through Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Dagger (Programmable CI) + OpenAI Agents SDK FAQ

Common questions about integrating Dagger (Programmable CI) MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.

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