MCP Integration is for teams that need a result they can measure. Model Context Protocol (MCP) is the new universal standard — championed by Anthropic and adopted by Open AI, Google, and Microsoft — for connecting AI models to external tools and data. Instead of building a custom integration for every AI model separately, MCP lets you build once and connect to everything. We design and deploy production MCP servers that give AI models safe, controlled access to your company's data and capabilities.
A typical engagement includes Custom MCP Servers, Database MCP Connectors, and Saa S Tool Integrations. Delivery focuses on Tool Mapping Session and MCP Schema Design. You also get Works with Claude, GPT, Gemini & Cursor, Build once, no re-integration needed, and Full security & audit logging.
Senior engineers who have shipped similar systems do the work. Common technical work includes Adopted by Every Major AI Lab, Build Once, Connect Everywhere, and Secure by Design. Open the sections below for scope, or contact us with the outcome you need.
We build MCP servers that expose your internal tools, databases, and business logic as structured capabilities any AI model can call — search your CRM, query your database, create tickets, send emails.
Give AI models read/write access to Postgre SQL, My SQL, Mongo DB, and other databases with row-level security, rate limiting, and audit logging built in.
MCP connectors for Slack, Notion, Jira, Salesforce, Hub Spot, Git Hub, and Linear — letting AI agents interact with your existing toolstack without custom API plumbing.
Centralised MCP gateway architecture for large organisations — a single secure endpoint that AI models connect to, with authentication, logging, and access control per team.
Anthropic created MCP. Open AI, Google Deep Mind, and Microsoft have all adopted it as the standard. Any AI model your business uses will support MCP — this investment pays dividends forever.
One MCP server works with Claude Desktop, Chat GPT, Cursor, Cline, and any other MCP client — no re-integration as the AI landscape evolves.
MCP enforces explicit capability declarations and user consent — AI models can only do exactly what your MCP server exposes, with a full audit trail of every action.
MCP is the connective tissue of AI agent systems. Agents use MCP to interact with the world — building your MCP layer now means your future agents are ready to act.
We inventory your internal systems and identify which capabilities would deliver the most value when exposed to AI models.
We design clean, well-typed tool schemas that make it easy for AI models to call your capabilities correctly and interpret responses accurately.
Every MCP server we build includes authentication, per-tool permission scopes, rate limiting, and complete request/response logging.
Full integration test suite and a developer guide so your team can extend the MCP server as your toolstack grows.
Each engagement is scoped to your goals, but most projects include Custom MCP Servers, Database MCP Connectors, Saa S Tool Integrations, and Enterprise MCP Gateways. We tailor deliverables to your product stage, team capacity, and business priorities.
Project timelines depend on complexity, integrations, and existing systems. Most engagements start with discovery and scoped planning, followed by iterative delivery milestones so you can review progress and ship value early.
Our stack is chosen based on your context, and commonly includes Adopted by Every Major AI Lab, Build Once, Connect Everywhere, Secure by Design, and Powers Agentic Workflows. We prioritize maintainability, performance, and long-term ownership by your internal team.
We follow a delivery process centered on Tool Mapping Session, MCP Schema Design, and Security & Permissions Layer and back it with Works with Claude, GPT, Gemini & Cursor, Build once, no re-integration needed, and Full security & audit logging. You receive clear documentation, production-ready handover, and ongoing support options after launch.