I help businesses implement Model Context Protocol (MCP) servers to support advanced AI integrations. MCP establishes a scalable, structured way for AI models, LLM-powered agents, and applications to exchange real-time context, ensuring reliable, consistent, and intelligent AI interactions.
My Expertise:
✅ Setting up robust MCP servers to enable structured context sharing between AI agents, APIs, and applications.
✅ Seamless MCP integration with existing software systems, allowing AI components to operate with full context awareness without major architecture changes.
✅ Building secure, scalable MCP-compatible infrastructure using Docker, Kubernetes, and modern cloud platforms.
✅ Integrating LLM frameworks like LangChain, ReAct, LangGraph with MCP for reliable context retention and intelligent task execution.
✅ Powering AI systems with RAG pipelines, vector databases (Pinecone, Chroma, Weaviate), and knowledge graphs, all accessible through MCP.
✅ Customizing MCP deployments for domain-specific AI use cases across industries like finance, healthcare, retail, logistics, and more.
✅ Providing complete technical documentation, deployment automation, and ongoing support for MCP environments.
What Sets Me Apart:
🔥 Hands-on expertise blending AI, LLMs, and MCP for real-world production systems.
🔥 Deep technical knowledge of AI architecture, context handling, and scalable infrastructure.
🔥 Business-driven approach ensuring MCP integration delivers measurable improvements to AI reliability and user experience.
🔥 Focus on security, scalability, and future-proof design for AI-ready systems.
🔥 Clear communication, transparent project management, and full technical ownership.
If you're building AI solutions that demand context retention, consistent memory, and intelligent coordination across systems. I deliver the right technical foundation with MCP to make it happen.