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Model Context Protocol (MCP) Integration Services

Give your AI secure access to your whole stack.

Seamless integration between AI applications and your enterprise tools, APIs, databases and external services - via the open Model Context Protocol.

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An AI model is only as useful as what it can reach. MCP is the standard way to safely connect models to your tools and data.

We build and integrate MCP servers for your internal systems - databases, CRMs, ticketing, file stores, custom APIs - and connect them to your AI agents with authentication, permissions and auditing engineered in. The result is an integration layer you build once and reuse everywhere.

What we build

An integration layer built once, reused everywhere

Standardised connectors replace a tangle of bespoke integrations.

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    Custom MCP servers

    We build MCP servers that expose your internal tools, databases and APIs to AI applications safely.

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    Tool & data connectors

    Connect models to CRMs, ticketing, file stores, search and bespoke systems through a consistent protocol.

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    Secure access control

    Authentication, scoped permissions and least-privilege access so AI reaches only what it should.

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    Client integration

    Wire MCP servers into your agents, assistants and AI apps - including Claude, IDEs and custom clients.

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    Auditing & governance

    Full logging of tool calls and data access for security review and compliance.

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    Reusable & maintainable

    Standardised connectors that reduce integration sprawl and are easy to extend as needs grow.

How we deliver

A path from idea to production

A pragmatic engagement model that de-risks adoption and gets a working system in front of your users fast.

  • 01

    Systems inventory

    We map the tools, data and APIs your AI needs to reach, and the access rules around them.

  • 02

    Server design

    We design MCP servers with the right tools, scopes and permission model for each system.

  • 03

    Build & secure

    We implement the servers with authentication, guardrails and auditing, and test against real clients.

  • 04

    Connect & operate

    We integrate with your AI apps and agents, then monitor usage, access and reliability.

Tools & stack

Technologies we work with

We stay model- and vendor-flexible, choosing the stack that fits your data, budget, and compliance needs.

  • Model Context Protocol
  • Anthropic Claude
  • MCP SDKs (Python / TypeScript)
  • OAuth / SSO
  • REST & GraphQL APIs
  • Databases
  • Internal tooling
  • Docker / cloud hosting

Where it fits

Use cases & industries

Whenever you want AI to work with your systems without rebuilding integrations for every tool.

  • Agent tooling

    Give agents governed access to internal systems through reusable connectors.

  • Enterprise assistants

    Let assistants read and act across CRMs, tickets and file stores.

  • Developer workflows

    Connect AI coding tools to your databases, repos and services.

  • Data access

    Expose databases to AI safely, with permissions and audit.

  • Cross-tool automation

    One protocol linking many systems into AI-driven workflows.

  • Vendor AI integration

    Connect third-party AI products to your stack via a standard interface.

Common questions

The Model Context Protocol is an open standard for connecting AI models to external tools and data. Think of it as a universal adapter, so you build a connector once and any compatible AI app can use it.

Handled correctly, yes. We enforce authentication, least-privilege scopes and full auditing so AI reaches only the specific tools and data you approve.

MCP is model- and client-agnostic. We build servers for your systems and connect them to Claude, custom agents, IDEs and other MCP-compatible clients.

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