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samples: add agentic #22938

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samples: add agentic
craig-osterhout Jun 27, 2025
d5f8c38
update repo and samples
craig-osterhout Jul 7, 2025
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2 changes: 1 addition & 1 deletion content/reference/samples/_index.md
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## Other samples

[AI/ML](../samples/ai-ml.md) \| [Cloudflared](../samples/cloudflared.md) \| [Elasticsearch / Logstash / Kibana](../samples/elasticsearch.md) \| [Minecraft](../samples/minecraft.md) \| [NGINX](../samples/nginx.md) \| [Pi-hole](../samples/pi-hole.md) \| [Plex](../samples/plex.md) \| [Traefik](../samples/traefik.md) \| [WireGuard](../samples/wireguard.md)
[Agentic AI](../samples/agentic-ai.md) \| [AI/ML](../samples/ai-ml.md) \| [Cloudflared](../samples/cloudflared.md) \| [Elasticsearch / Logstash / Kibana](../samples/elasticsearch.md) \| [Minecraft](../samples/minecraft.md) \| [NGINX](../samples/nginx.md) \| [Pi-hole](../samples/pi-hole.md) \| [Plex](../samples/plex.md) \| [Traefik](../samples/traefik.md) \| [WireGuard](../samples/wireguard.md)

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---
title: Agentic AI samples
description: Docker samples for agentic AI.
service: agentic-ai
---
96 changes: 95 additions & 1 deletion data/samples.yaml
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description: Get started with AI and ML using Docker, Neo4j, LangChain, and Ollama
services:
- python
- aiml
- aiml
# Agentic AI ----------------------------
- title: Agent-to-Agent
url: https://github.com/docker/compose-for-agents/tree/main/a2a
description: >
This app is a modular AI agent runtime built on Google's Agent
Development Kit (ADK) and the A2A (Agent-to-Agent) protocol. It wraps a
large language model (LLM)-based agent in an HTTP API and uses
structured execution flows with streaming responses, memory, and tools.
It is designed to make agents callable as network services and
composable with other agents.
services:
- python
- aiml
- agentic-ai
- title: ADK Multi-Agent Fact Checker
url: https://github.com/docker/compose-for-agents/tree/main/adk
description: >
This project demonstrates a collaborative multi-agent system built with
the Agent Development Kit (ADK), where a top-level Auditor agent coordinates
the workflow to verify facts. The Critic agent gathers evidence via live
internet searches using DuckDuckGo through the Model Context Protocol (MCP),
while the Reviser agent analyzes and refines the conclusion using internal
reasoning alone. The system showcases how agents with distinct roles and
tools can collaborate under orchestration.
services:
- python
- aiml
- agentic-ai
- title: DevDuck agents
url: https://github.com/docker/compose-for-agents/tree/main/adk-cerebras
description: >
A multi-agent system for Go programming assistance built with Google
Agent Development Kit (ADK). This project features a coordinating agent
(DevDuck) that manages two specialized sub-agents (Bob and Cerebras)
for different programming tasks.
services:
- python
- aiml
- agentic-ai
- title: Agno
url: https://github.com/docker/compose-for-agents/tree/main/agno
description: >
This app is a multi-agent orchestration system powered by LLMs (like Qwen
and OpenAI) and connected to tools via a Model Control Protocol (MCP)
gateway. Its purpose is to retrieve, summarize, and document GitHub
issues—automatically creating Notion pages from the summaries. It also
supports file content summarization from GitHub.
services:
- python
- aiml
- agentic-ai
- title: CrewAI
url: https://github.com/docker/compose-for-agents/tree/main/crew-ai
description: >
This project showcases an autonomous, multi-agent virtual marketing team
built with CrewAI. It automates the creation of a high-quality, end-to-end
marketing strategy — from research to copywriting — using task delegation,
web search, and creative synthesis.
services:
- python
- aiml
- agentic-ai
- title: SQL Agent with LangGraph
url: https://github.com/docker/compose-for-agents/tree/main/langgraph
description: >
This project demonstrates a zero-config AI agent that uses LangGraph to
answer natural language questions by querying a SQL database — all
orchestrated with Docker Compose.
services:
- python
- aiml
- agentic-ai
- title: Spring AI Brave Search Example - Model Context Protocol (MCP)
url: https://github.com/docker/compose-for-agents/tree/main/spring-ai
description: >
This example demonstrates how to create a Spring AI Model Context Protocol
(MCP) client that communicates with the Brave Search MCP Server. The
application shows how to build an MCP client that enables natural language
interactions with Brave Search, allowing you to perform internet searches
through a conversational interface. This example uses Spring Boot
autoconfiguration to set up the MCP client through configuration files.
services:
- java
- aiml
- agentic-ai
- title: MCP UI with Vercel AI SDK
url: https://github.com/docker/compose-for-agents/tree/main/a2a
description: >
Start an MCP UI application that uses the Vercel AI SDK to provide a
chat interface for local models, provided by the Docker Model Runner,
with access to MCPs from the Docker MCP Catalog.
services:
- aiml
- agentic-ai