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Run AI agents through OpenAI-compatible APIs with memory and multi-step workflows.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "agents-mcp" yet — see the docs or source repo.
Create a customer support agent with the system prompt: "You are a professional SaaS support agent. Keep answers concise and prioritize step-by-step instructions." Use a GPT-4 compatible model, enable persistent memory, and answer: "How do I reset a team member's password?"
Returns the agent's support response and preserves memory settings for future conversations.
Configure a three-step pipeline agent: first research "AI workplace trends in 2025," then summarize them into 5 key points, and finally draft a Chinese blog post for a product website in a professional but accessible tone.
Outputs step-by-step results, including research notes, key points, and a blog draft.
Use a swarm with a researcher agent and a writer agent: the researcher analyzes "the main barriers to AI customer support adoption for SMBs," then the writer produces a 300-word Chinese summary highlighting business value and implementation advice.
Returns the collaborative analysis results and a concise summary from the agent swarm.
Run a fully local multi-agent AI system with predefined workflows via MCP.
Run persistent agent teams and durable workflows with memory, schedules, and goals.
Build AI agent workflows and automate tasks using MCP-connected services.
Give MCP agents persistent memory and long-running monitoring across sessions.
Give AI agents persistent memory with semantic search and automatic memory management.
Coordinate specialized AI agents for software development, review, testing, and task tracking.