We build Model Context Protocol (MCP) agents that connect AI models to your real data, systems, and workflows — turning language models into genuinely useful business tools.
Generic AI chatbots can answer questions — but they can't access your CRM, run a database query, trigger a workflow, or act on live business data. Model Context Protocol (MCP) changes that. It's a standard protocol that lets AI models interact with tools and data sources through a secure, extensible interface.
We design and build MCP servers that expose your internal systems — databases, APIs, file stores, SaaS tools — to AI models in a controlled, governed way. The result is an AI assistant that genuinely understands your business context and can take meaningful action within it.
From a single MCP server connecting an AI to your database, to a full multi-agent system spanning your entire organisation.
We build purpose-built MCP servers that expose your data and tools to AI models in a clean, type-safe, well-documented way — using the official MCP SDK.
We integrate Claude, GPT-4, and other leading models into your products and internal tools, with carefully engineered system prompts and guardrails.
MCP servers that connect AI to your PostgreSQL database, REST APIs, SharePoint, Jira, Salesforce, or any internal system — with proper authentication and row-level permissions.
Orchestrated agent systems where specialised agents collaborate on complex tasks — each with a defined role, tools, and data access scope.
We enforce authentication, authorisation, input validation, and comprehensive audit logging so your agents operate within defined boundaries.
Structured logging of every tool call and model response. Dashboards to track usage, latency, and failure rates so you understand what your agents are actually doing.
A practical process for turning AI ideas into working, deployed systems.
We identify which business processes will genuinely benefit from AI agents and where the ROI is strongest.
We design the agent topology: which tools it needs, what data it accesses, how it authenticates, and how it hands off to humans when needed.
We develop the MCP server, tool implementations, and resource handlers — with full test coverage and documentation.
End-to-end testing with real data, edge case handling, and adversarial prompt testing to validate security boundaries.
Containerised deployment with monitoring, logging, and runbooks. We stay involved until you're confident running it independently.
Tell us about the workflow you want to automate or the data you want AI to access. We'll tell you if MCP is the right solution and how to build it.
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