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New — MCP Consulting

Put Your Data Directly in AI's Hands

Model Context Protocol (MCP) lets AI assistants query your live data infrastructure. We help you design, implement, and govern MCP servers that make your AI stack genuinely useful.

MCP Server DesignAI-Ready Data LayersGovernance & Security
MCPModel Context Protocol
10+Years Data Expertise
50+Happy Clients

What is MCP?

Model Context Protocol is an open standard that allows AI assistants like Claude to securely connect to your databases, warehouses, and BI tools in real time — turning your data infrastructure into a live context source for AI reasoning.

Instead of exporting CSVs or writing manual queries, your team can ask natural language questions and get answers grounded in your actual data.

What We Deliver

End-to-end MCP consulting from architecture to production deployment.

MCP Server Design

Architect secure, performant MCP servers that expose the right data to your AI tools without over-permissioning.

Data Layer Readiness

Prepare your warehouse and semantic layer for AI consumption — clean models, clear naming, documented metrics.

Governance & Security

Define access controls, audit trails, and data contracts so AI access is both powerful and safe.

AI Tool Integration

Connect Claude, Cursor, and other MCP-compatible tools to your stack so your team works smarter from day one.

How MCP Consulting Works

A structured approach from assessment to live AI-powered data access.

01

Data Architecture Review

We audit your current stack — warehouse, semantic layer, BI tools — to identify the best MCP entry points and data readiness gaps.

02

MCP Server Implementation

We design and deploy MCP servers with proper authentication, scoped permissions, and optimised query patterns.

03

Team Enablement

Your team learns to leverage AI-powered data access effectively, with guardrails that ensure quality and governance.

Ready to Make Your Data AI-Accessible?

Let's design an MCP architecture that connects your AI tools to your real data — securely and scalably.