I will build production ai agents with claude code, langchain, mcp

Your chatbot demo works. In production it forgets context, hallucinates tool calls, and can't touch your real systems.

That gap between a cool LLM demo and an AI agent that actually runs your business logic is exactly what I close.

I build autonomous AI agents using Claude Code, LangChain, and the Model Context Protocol (MCP) agents that read your data, call your APIs, execute multi-step tasks, and hand off to humans only when they should. Whether you need a single-purpose task agent, a multi-tool orchestrator, or a full AI SaaS MVP wrapping GPT/Gemini/Claude, I design the agent architecture, wire the tool integrations, and ship it working not a proof-of-concept that breaks on the second edge case.

What you get:

• Custom AI agent logic (Claude Code / LangChain) mapped to your actual workflow, not a generic template
• MCP server/tool integrations so your agent can safely call real APIs, databases, and internal systems
• Python automation + scraping layer for data your agent needs to act on
• Full-stack delivery when needed React/Next.js frontend, Django/DRF backend, deployed with CI/CD
• Retool dashboard for human-in-the-loop review, approvals, or monitoring