@@ -350,4 +350,98 @@ samples:
350350 description : Get started with AI and ML using Docker, Neo4j, LangChain, and Ollama
351351 services :
352352 - python
353- - aiml
353+ - aiml
354+ # Agentic AI ----------------------------
355+ - title : Agent-to-Agent
356+ url : https://github.com/docker/compose-for-agents/tree/main/a2a
357+ description : >
358+ This app is a modular AI agent runtime built on Google's Agent
359+ Development Kit (ADK) and the A2A (Agent-to-Agent) protocol. It wraps a
360+ large language model (LLM)-based agent in an HTTP API and uses
361+ structured execution flows with streaming responses, memory, and tools.
362+ It is designed to make agents callable as network services and
363+ composable with other agents.
364+ services :
365+ - python
366+ - aiml
367+ - agentic-ai
368+ - title : ADK Multi-Agent Fact Checker
369+ url : https://github.com/docker/compose-for-agents/tree/main/adk
370+ description : >
371+ This project demonstrates a collaborative multi-agent system built with
372+ the Agent Development Kit (ADK), where a top-level Auditor agent coordinates
373+ the workflow to verify facts. The Critic agent gathers evidence via live
374+ internet searches using DuckDuckGo through the Model Context Protocol (MCP),
375+ while the Reviser agent analyzes and refines the conclusion using internal
376+ reasoning alone. The system showcases how agents with distinct roles and
377+ tools can collaborate under orchestration.
378+ services :
379+ - python
380+ - aiml
381+ - agentic-ai
382+ - title : DevDuck agents
383+ url : https://github.com/docker/compose-for-agents/tree/main/adk-cerebras
384+ description : >
385+ A multi-agent system for Go programming assistance built with Google
386+ Agent Development Kit (ADK). This project features a coordinating agent
387+ (DevDuck) that manages two specialized sub-agents (Bob and Cerebras)
388+ for different programming tasks.
389+ services :
390+ - python
391+ - aiml
392+ - agentic-ai
393+ - title : Agno
394+ url : https://github.com/docker/compose-for-agents/tree/main/agno
395+ description : >
396+ This app is a multi-agent orchestration system powered by LLMs (like Qwen
397+ and OpenAI) and connected to tools via a Model Control Protocol (MCP)
398+ gateway. Its purpose is to retrieve, summarize, and document GitHub
399+ issues—automatically creating Notion pages from the summaries. It also
400+ supports file content summarization from GitHub.
401+ services :
402+ - python
403+ - aiml
404+ - agentic-ai
405+ - title : CrewAI
406+ url : https://github.com/docker/compose-for-agents/tree/main/crew-ai
407+ description : >
408+ This project showcases an autonomous, multi-agent virtual marketing team
409+ built with CrewAI. It automates the creation of a high-quality, end-to-end
410+ marketing strategy — from research to copywriting — using task delegation,
411+ web search, and creative synthesis.
412+ services :
413+ - python
414+ - aiml
415+ - agentic-ai
416+ - title : SQL Agent with LangGraph
417+ url : https://github.com/docker/compose-for-agents/tree/main/langgraph
418+ description : >
419+ This project demonstrates a zero-config AI agent that uses LangGraph to
420+ answer natural language questions by querying a SQL database — all
421+ orchestrated with Docker Compose.
422+ services :
423+ - python
424+ - aiml
425+ - agentic-ai
426+ - title : Spring AI Brave Search Example - Model Context Protocol (MCP)
427+ url : https://github.com/docker/compose-for-agents/tree/main/spring-ai
428+ description : >
429+ This example demonstrates how to create a Spring AI Model Context Protocol
430+ (MCP) client that communicates with the Brave Search MCP Server. The
431+ application shows how to build an MCP client that enables natural language
432+ interactions with Brave Search, allowing you to perform internet searches
433+ through a conversational interface. This example uses Spring Boot
434+ autoconfiguration to set up the MCP client through configuration files.
435+ services :
436+ - java
437+ - aiml
438+ - agentic-ai
439+ - title : MCP UI with Vercel AI SDK
440+ url : https://github.com/docker/compose-for-agents/tree/main/a2a
441+ description : >
442+ Start an MCP UI application that uses the Vercel AI SDK to provide a
443+ chat interface for local models, provided by the Docker Model Runner,
444+ with access to MCPs from the Docker MCP Catalog.
445+ services :
446+ - aiml
447+ - agentic-ai
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