Build the bridge between AI and your systems with MCP. We develop Model Context Protocol servers that give Claude and other AI models secure, structured access to your databases, APIs, and internal tools, the standard protocol for enterprise AI integration.
Proof-First Delivery
What We Offer
Each module is designed as a production block with integration boundaries, governance hooks, and measurable outcomes.
Custom MCP servers that expose your internal APIs, databases, and tools to AI models. TypeScript or Python implementations with proper schema definitions, input validation, and error handling.
Design the right tool abstractions for your AI workflows — what to expose, how to parameterize, and where to draw security boundaries. Tools that are useful to the AI without being dangerous.
Multi-server MCP architectures with authentication, rate limiting, audit logging, and monitoring. Connect multiple data sources through a governed MCP gateway.
Configure MCP servers for Claude Desktop, Claude Code, and API-based agents. End-to-end integration from MCP server to production AI application.
Integrate MCP servers with LangChain, CrewAI, and custom agent architectures. Give your multi-agent systems standardized access to tools and data.
Convert existing ad-hoc LLM tool integrations to MCP standard. Reduce maintenance burden and gain compatibility with the growing MCP ecosystem.
We adopted MCP from its Anthropic launch. Production experience building MCP servers for databases, CRMs, document systems, and custom business APIs.
Deep experience with Claude API, tool-use, and the Anthropic ecosystem. We understand how MCP fits into the broader Claude architecture.
MCP servers that enforce least-privilege access, validate all inputs, and log every tool invocation. Enterprise-ready from day one.
MCP server + agent architecture + frontend — we build the complete system, not just the protocol layer.
Delivery Proof
Selected engagements that show architecture depth, execution quality, and measurable business impact.
Delivery Advantages
Custom MCP servers that expose your internal APIs, databases, and tools to AI models. TypeScript or Python implementations with proper schema definitions, input validation, and error handling.
Design the right tool abstractions for your AI workflows — what to expose, how to parameterize, and where to draw security boundaries. Tools that are useful to the AI without being dangerous.
Multi-server MCP architectures with authentication, rate limiting, audit logging, and monitoring. Connect multiple data sources through a governed MCP gateway.
Configure MCP servers for Claude Desktop, Claude Code, and API-based agents. End-to-end integration from MCP server to production AI application.
FAQ
Tell us about your systems and AI goals — we'll design an MCP architecture that gives your AI secure, structured access to your data and tools.