I will claude ai agent mcp server rag pipeline claude code mcp developer


About this gig
Your business runs 24 hours. Your Claude agent should too.
You've reached the point where the bottleneck isn't strategy, it's the execution gap between your data and the decisions that need to be made on it. Leads sitting unscored. Invoices waiting to be extracted. Customer queries queuing overnight. Reports that should have been drafted before anyone logged in.
I build Claude API-powered agents that close that gap, autonomous systems that qualify, extract, route, draft, score, and schedule without a human in the loop.
What I deliver:
- Autonomous Agent Pipelines
- Custom MCP Servers
- RAG Knowledge Base Agents
- Document Intelligence Pipelines
- Production-Grade Everything
How we work together:
Step 1: You share your stack, your bottleneck, and your target outcome.
Step 2: I return a scoped architecture proposal with cost-per-run estimates before build begins.
Step 3: We build milestone by milestone, with documented checkpoints, until your system is running.
What I need from you: API access, a clear goal, and responsive feedback during the build week.
Ready to see if this fits your situation? Send me your current setup for a direct feasibility review before ordering.
Get to know Williams
I build custom Claude MCP servers, SKILL md workflows
- FromNigeria
- Member sinceMay 2026
- Avg. response time2 hours
- Last delivery2 weeks
Languages
English, Spanish, French
My Portfolio
FAQ
Can you connect Claude to my existing CRM, ERP, or internal platform?
Yes, this is exactly what MCP servers are for. I build custom MCP connectors that wrap your platform's REST API as callable Claude tools, so Claude reads and acts on your live data natively.
How do I know the Claude agent won't hallucinate or return unreliable outputs in production?
Every pipeline I deliver uses structured output validation with Pydantic v2 schemas. If Claude's response fails validation, it retries once with corrective context, then raises a clean structured error, not a silent failure you discover later.
Will the token costs spiral out of control as usage scales?
No, cost management is designed in before the first line is written
What's the difference between what you deliver and a basic n8n + ChatGPT automation?
Three things: validation, observability, and evals. A basic automation has no schema enforcement (so malformed outputs break downstream), no production monitoring (so failures are invisible), and no regression testing (so you don't know if a model update changed the behavior).
Can you build a multi-agent system where different Claude agents handle different parts of my workflow?
Yes, multi-agent orchestration is a core part of what I build.
Do you use LangChain, and is it required?
I use the Anthropic Agent SDK for most builds, not LangChain by default.

