Add code execution capability to AG2 agents using LocalCommandLineCodeExecutor or Docker. Use when the user wants agents that can write and run Python code.
ag2ai/cursor-plugin
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Add safety guardrails to AG2 agents using LLMGuardrail and RegexGuardrail. Use when the user wants to enforce safety constraints, filter PII, or redirect off-topic responses.
Wire a Model Context Protocol (MCP) server into AG2 agents using create_toolkit. Use when the user wants to connect external tools via MCP.
Build an AG2 handoff-driven workflow with DefaultPattern, agent handoffs, context variables, and routing. Use when the user wants customer service routing, state-machine workflows, or explicit agent-to-agent transitions.
Build a Retrieval-Augmented Generation (RAG) agent using AG2's RetrieveUserProxyAgent with vector database support. Use when the user wants agents that can query documents or knowledge bases.
Build an AG2 ReasoningAgent that uses tree-of-thought reasoning with beam search, MCTS, or LATS strategies. Use when the user needs advanced reasoning for complex problem solving.
Build a complete web research agent team using AG2 with search tools, web crawling, and structured output. Use when the user wants a practical research or information-gathering workflow.
Scaffold a complete AG2 multi-agent team with agents, tools, group chat configuration, and an entry point. Use when the user wants to create a new multi-agent workflow from scratch.
Analyze AG2 agent conversation logs and code to diagnose issues like wrong speaker selection, tool call failures, infinite loops, or unexpected termination.
Add a properly typed and registered tool function to an existing AG2 agent setup. Generates the function with schema, type annotations, and correct registration on both caller and executor agents.