MCP Server Development
Expose your systems, data, and tools to Claude and AI agents as a secure MCP server — with auth, access control, and logging.
How do you expose internal systems to Claude and other AI agents safely?
Caffinix builds MCP (Model Context Protocol) servers that expose a company's systems, data and tools to Claude and other AI agents as properly authenticated, access-controlled and logged endpoints. It is auth, transport and API design done deliberately, so agents call real tools rather than guessing from scraped context.
We expose your systems, data, and tools to Claude and other AI agents as a secure MCP server — so agents can actually use your product instead of guessing about it. MCP is auth, transport, and API design done right: your tools, safely callable, with access control and logging, not a scraped approximation.
What you get
- ✓Your systems and APIs exposed to AI agents as a secure, standards-compliant MCP server
- ✓Auth, scoped access, and logging so agents get exactly the access you allow
- ✓Deployment on your infrastructure with docs your team can extend
Who it's for
- —SaaS teams that want their product usable by Claude and AI agents
- —Internal platform teams standardizing how agents reach company tools
- —Companies whose data lives behind APIs that agents currently can't touch
How we work
A real engagement, week by week.
- 1Week 1
Surface + auth design
- Decide which tools and data to expose — and which never to
- Design auth, scopes, and rate limits per tool
- Map the MCP transport and API contracts
- 2Week 2
Build the server
- Implement the MCP server over your systems and APIs
- Add access control, input validation, and structured logging
- Test tool-calling against a real agent
- 3Week 3–4
Harden + deploy
- Add multi-tenant isolation and cost / access controls where scoped
- Deploy on your infra with monitoring
- Hand over docs so your team can add tools
Why us
Why us.
Senior backend is our lane — MCP is auth, transport, and API design, exactly the hard part the wrapper crowd skips.
We run our own gateway and tooling, so this is a pattern we operate, not one we're learning on your dime.
Qualified MCP supply is near-zero right now — a timing wedge, and we're already deep in it.
Common questions
Things prospects ask first.
Any system with an API — your product, internal tools, databases behind a service layer. We design exactly which tools and scopes agents can reach, and which they can't.
That's the core of the work: auth, scoped access, validation, logging, and multi-tenant isolation where needed. We treat it as a production API, not a demo endpoint.
Yes. MCP is the standard Claude uses; we build to spec so it works with Claude and other MCP-compatible agents.
Also booking now
- →AI Agents & RAG ChatbotsProduction RAG agents grounded in your real data, with tool-calling and a measured hallucination rate.
- →AI Agent Reliability & EvalsOn-call reliability, eval suites, observability, and model/cost optimization for production AI agents.
- →AI Integration for Existing SoftwareLLM features inside a real backend: streaming, auth, rate limits, retries, fallback, and cost control.
- →Fractional AI LeadA senior AI engineer and product lead on your team part-time — architecture, build oversight, and hands-on delivery, without a full-time hire.
- →AI Workflow Automationn8n, Make, or Python pipelines that replace the manual handoffs eating your team's hours — with AI steps only where they earn it.
- →AI-Powered Product & MVP BuildsWeb and mobile products with AI built in, launched in 4–8 weeks — scoped hard to the core loop, on a stack that survives past launch.
Ready to start this?
Tell us what you're trying to ship. A senior engineer replies within one business day, and the first call is 20 minutes — we'll say straight whether it's a fit.
Prefer email? contact@caffinix.com