mcp-development
MCP Server Development
Connect Claude, ChatGPT, and AI tools to your internal systems.
Production MCP servers connecting LLMs to internal databases, APIs, CRMs, and legacy software. TypeScript, OAuth, rate limiting, monitoring — built for real workloads, not demos.
Catalogue
Internal Tool MCP Servers
Connect AI assistants to your databases, dashboards, and ops tools. Let Claude query your data, trigger workflows, and surface insights without leaving the chat.
Customer-Facing AI Integrations
Embed AI capabilities into your product. Give your users AI-powered features that work with their data through clean, secure MCP interfaces.
Multi-System Orchestration
AI that works across your entire stack. One MCP server that bridges CRM, finance, ops, and communications — so AI sees the full picture.
Legacy System Bridges
Make old systems AI-accessible without rewriting them. We build MCP layers on top of databases, FTP feeds, SOAP APIs, and file-based integrations.
Process
How the work runs
01
Architecture call
We map your systems and identify high-value AI integration points. You leave with a clear picture of what MCP can do for your specific stack.
02
Build
Iterative development with your team. TypeScript, full type safety, comprehensive error handling, OAuth where needed. Typically 2–4 weeks for the first MCP server.
03
Deploy and handoff
Production deployment with monitoring, documentation, and team walkthrough. Your devs can maintain and extend it — no vendor lock-in.
Questions
What is MCP and why should I care?
Model Context Protocol is an open standard that lets AI tools (Claude, ChatGPT, etc.) connect to external systems. Instead of copy-pasting data into AI chats, MCP lets AI pull live data from your databases, trigger actions in your tools, and work with your actual business context. It turns AI from a text generator into a real operational tool.
How long does a typical MCP server take to build?
2–4 weeks for a production-ready server with 10–30 tools, full authentication, error handling, and documentation. Simpler servers (5–10 tools, single system) can ship in under a week.
Do we need to rebuild our existing systems?
No. MCP servers are a bridge layer — they connect AI to your existing systems via their APIs, databases, or file interfaces. We work with what you have, including legacy systems with no API.
How does pricing work?
Every MCP build is scoped to your stack and the systems we are connecting. We share a detailed proposal with a fixed scope and timeline before work begins — no hidden fees, no surprises. Book a call and we will come back with a plan.
Can our in-house devs maintain it?
Yes. We build in TypeScript with full type safety, comprehensive documentation, and test coverage. We do a walkthrough with your team and you own the code completely.
What AI tools does this work with?
MCP is supported by Claude (Anthropic), and the ecosystem is growing fast. We also build custom integrations for OpenAI, Gemini, and other providers when MCP isn't the right fit.