I will build a custom mcp server for claude code and ai agents

MCP is a standard way to give an AI client access to your tools and data. You need one if you want Claude or Cursor to read and write in your systems instead of you pasting context by hand. If a simple API call solves your problem, I'll tell you that.

Yes. The Model Context Protocol is client-agnostic. I test against the client you name and hand over the exact config block for it. If your team uses several, I set up all of them in the same order.

Yes. The server ships into your repo under your license, with a README and setup instructions. Source is in every package, never an extra. My own reusable internal libraries stay mine.

Yes. I build against your API contract or a staging environment, then hand over deployment instructions for your network. I don't need production credentials to write the server.

Yes, from Production MCP up. Docker image, deployment to your cloud, environment config, structured logging. I walk you through the deploy so your team can redeploy without me.

Go, Python or TypeScript. I recommend based on what your team already maintains, since the best server is one your engineers can read. Go when throughput and concurrency matter, Python when it sits next to existing ML code.

Yes. The usual problems are tool descriptions the model misreads, missing input validation, no auth scoping, and blocking handlers that hang the model mid-call. Send the repo and I'll tell you what's wrong before you order.

Yes. LangGraph agent workflows, vector search with Pinecone, and the backend services around them. MCP is usually one piece of a larger system and I can build the rest of it.