The MCP server that enables any AI agent to build production software autonomously
Works with any MCP-compatible AI—Claude, GPT-4, Gemini, or custom models. Marcus provides the rails, you choose the AI.
# MCP tools your agent will use register_agent(skills=["Python", "React"]) request_next_task() # Pull when ready report_progress(0.75) # Track progress report_blocker() # Get unstuck
No idle agents, no complex orchestration. Agents request tasks when ready. Marcus intelligently assigns based on skills and context.
# How agents work autonomously while project.has_tasks(): task = agent.request_next_task() result = agent.complete_task(task) agent.report_progress(result)
Every task completion teaches Marcus. Discover patterns that work, avoid common failures, and continuously improve agent performance.
# Train agents on best practices
patterns = marcus.analyze_successes()
prompt = marcus.generate_prompt(
role="backend",
learned_patterns=patterns
)
Built on Model Context Protocol—the emerging standard for AI agent communication. Your agents speak MCP? They work with Marcus. Future-proof your AI infrastructure.
MCP implementation →Not toy problems or demos. Marcus manages actual software projects. Every completed task improves future performance. Production-grade from day one.
How Marcus learns →