I will build a custom mcp server and langgraph multi agent systems


Sobre este Serviço
I design and build custom multi-agent AI systems using LangGraph and MCP (Model Context Protocol): real production systems, not demo scripts.
As a senior software engineer with 10+ years in Python (Django, FastAPI) and AWS infrastructure, I build agents that are reliable, observable, and ready for real users, not just a proof of concept.
What you get:
- Custom LangGraph multi-agent workflows: planning, tool-calling, human-in-the-loop
- Custom MCP servers connecting Claude, GPT, or your own LLM to your tools and data
- RAG pipelines grounded in your documents, database, or APIs
- Async orchestration (Celery/RabbitMQ) for long-running agent jobs
- Cloud deployment on AWS (ECS Fargate, Lambda) or Docker, with CI/CD
Why work with me:
Many "AI agent" gigs deliver a chatbot with extra steps. I bring real backend engineering: multi-tenant SaaS systems, HIPAA-regulated platforms, and agentic pipelines already live in production. You get someone who understands the AI layer and the infrastructure it has to run on.
Message me with your use case before ordering so I can scope the right package for it. Every agent build is different.
Conheça mais sobre Muhammad Farhan
PUT MY EFFORTS INTO YOUR BUSINESS
- A partir dePaquistão
- Membro desdejul. de 2022
- Responde em aprox.:1 hora
- Última entrega2 anos
Idiomas
Urdu, Inglês
Meu portfólio
Perguntas frequentes
What is MCP and why does my project need it?
MCP (Model Context Protocol) is an open standard for connecting AI models like Claude to your tools, databases, and files in a structured, secure way. If you want an AI agent that can actually read your data or take actions in your systems rather than just chat, MCP is usually the right foundation.
Do you deploy the system, or just hand over the code?
Both. I deploy to AWS (ECS Fargate, Lambda) or Docker with CI/CD included in Standard and Premium packages, so you get a running system, not just a repo.
What's the difference between a simple chatbot and a multi-agent LangGraph system?
A chatbot answers one message at a time. A LangGraph multi-agent system uses specialized agents (planner, researcher, tool-caller) to handle multi-step tasks with memory and human-in-the-loop checkpoints. More than one decision point? Multi-agent is the better fit.

