AI Tools & Platforms

MCP Server Development

Agentik OS specializes in designing and shipping production-grade Model Context Protocol (MCP) servers that extend AI capabilities far beyond standard tooling. Our engineers have built MCP integrations across dozens of domains: connecting Claude to proprietary databases and internal REST APIs, creating bidirectional sync layers between AI agents and SaaS platforms like Notion, Linear, and Salesforce, and building multi-tenant MCP gateways serving up to 50 concurrent agents with sub-200ms response latency. We work across the full MCP specification, implementing resource providers, tool handlers, prompt templates, and sampling endpoints with strict type safety and structured error surfaces that models can interpret and act on. Past projects include a real-time inventory lookup server for a mid-size e-commerce client that reduced hallucination errors by 73%, a legal document retrieval system with row-level access control, and an internal analytics gateway that eliminated a class of manual reporting tasks entirely. Servers are deployed on Cloudflare Workers, AWS Lambda, or dedicated VPS infrastructure based on your latency and cost profile.

View Pricing

Benefits

Why Choose Our MCP Server Development

Concrete advantages that directly impact your bottom line.

Connect any AI model to internal systems without modifying prompts or model behavior

Reusable, versioned tool definitions that work across multiple agents and workflows simultaneously

Production-ready authentication, rate limiting, and error handling shipped from day one

Dramatic reduction in prompt complexity by moving context retrieval into dedicated server logic

Full observability with per-tool invocation logs, latency histograms, and error rate dashboards

Our Approach

How We Help

A structured approach to delivering measurable results.

Architecture and Specification

We audit your existing systems and design the optimal MCP server architecture: which tools to expose, how to model resources, and whether you need a single multi-tool server or a federation of domain-specific servers with a routing layer.

Build and Integration

Our engineers implement the full MCP server using TypeScript or Python SDKs, including OAuth and API key middleware, connection pooling for databases, retry logic for downstream services, and error surfaces structured for AI consumption rather than human debugging.

Deployment and Monitoring

We deploy to your preferred infrastructure using zero-downtime rollout strategies, configure structured logging for every tool invocation, and deliver dashboards that surface usage patterns, per-tool latency, and error rates so you can iterate with confidence.

Related Expertise