Connecting Claude to your business systems: an MCP guide for UK leaders

The Model Context Protocol (MCP) is an open standard that lets an AI assistant such as Claude connect to the systems where your data and tools already live, including document stores, business applications, and databases. Instead of staff copying and pasting context into a chat window, MCP gives Claude a governed, two-way connection to a named system so it can retrieve the right information and, where you allow it, take an action. For a UK leader, the decision is not whether MCP is clever. It is which systems are worth connecting, what a credible rollout looks like, and where the security boundary sits.

This briefing is written for IT and operations leaders scoping a Claude rollout, not for developers. It assumes you already understand what a large language model does and want to decide where MCP earns its place.

What the Model Context Protocol actually is

Anthropic introduced MCP as an open standard in November 2024 and has since contributed it to a foundation under the Linux Foundation, developed alongside other AI vendors rather than held proprietary. That governance point matters commercially: MCP is not a lock-in mechanism unique to one supplier. The same protocol is supported across a range of AI clients and development tools, so an integration built against it is reusable rather than throwaway.

The architecture is deliberately simple. A system exposes its data and capabilities through an MCP server. An AI application, the MCP client, connects to that server. Claude is one such client. The server decides what it exposes and under what credentials, and the client decides what it asks for. The practical effect is that Claude can read from and write to a connected system through a single, consistent interface, rather than each integration being a bespoke piece of engineering that someone has to maintain.

Two deployment shapes are worth separating in your mind. Local MCP servers run on a user's own machine and are supported across Claude's desktop application, which suits early experimentation and single-user workflows. Managed, organisation-wide connectors are the production shape: on the Claude Enterprise plan, Anthropic provides connectors for common workplace systems including Google Drive, Gmail, Google Calendar, Microsoft 365, Slack, and GitHub, so Claude can retrieve context from documents, email, calendars, and team channels without manual uploads. Remote MCP servers extend the same model to systems you host yourself.

Which business systems deserve a connection

Connecting everything is the wrong instinct. Each connection adds attack surface, governance overhead, and a maintenance commitment. The systems worth connecting share three traits: they hold information staff repeatedly need, that information changes often enough that a static export goes stale, and the work of fetching it by hand is a measurable drain.

In most UK organisations, that points to a short list. A document or knowledge store (SharePoint, Google Drive, a Confluence space) is usually the highest-value first connection, because internal knowledge retrieval is the lowest-risk, highest-frequency use of Claude. Email and calendar follow closely for roles that live in their inbox. A CRM or case management system is the next tier, valuable but more sensitive because it holds personal data. Ticketing and code repositories matter for technical teams. Core finance and HR systems sit further out: high value, but the data sensitivity and the consequences of a wrong action mean they warrant a connection only once the governance pattern is proven elsewhere.

A useful test before connecting any system: if Claude retrieved the wrong record from it, or wrote a wrong value to it, what is the worst credible outcome? Where that answer is "a slightly off first draft", connect early. Where it is "a customer receives incorrect information" or "a financial record is altered", connect late, read-only first, and with human sign-off on any write.

What a credible rollout looks like

A rollout that survives contact with a security review tends to follow the same sequence. It starts with one read-only connection to a low-sensitivity knowledge store, used by a defined group, with the use case written down. It proves that the retrieval is accurate and that staff trust it. Only then does it add a second system, and only later does it permit Claude to take actions rather than just read.

Write access is the threshold that changes the risk profile. Reading from a system to inform a human is low-stakes. Letting Claude send the email, update the record, or raise the ticket is where bounded autonomy and human review have to be designed in deliberately. The credible pattern is to keep a human in the loop on any action with an external or financial consequence until you have an evidence base that says otherwise.

As a registered Anthropic Consulting Partner, The AI Consultancy scopes these rollouts the same way: connection by connection, lowest risk first, with the control framework written before the second system is added rather than after an incident. Buyers reasonably want to know that the people configuring access to their systems have vetted Claude expertise, which is the practical reason that credential is worth checking for in any supplier.

The security boundary

The most common leadership worry is that connecting Claude to internal systems hands a third party a key to everything. It does not, if the boundary is configured properly. An MCP server runs with whatever credentials you give it, so the boundary is set by scoping those credentials to least privilege: the connection should see only the data the use case needs, and nothing more. A connector to a single document library is not a connector to the whole tenant.

The Claude Enterprise plan adds the controls a UK IT function will expect around that boundary. These include single sign-on and SCIM for provisioning, audit logs that capture user actions and data access, custom data retention controls, customer-managed encryption keys held in your own cloud, and the option to keep inference within a defined region. Anthropic states that customer data from commercial deployments is not used to train its models. For organisations with data residency requirements, Claude can be deployed in-region through AWS Bedrock, Google Cloud Vertex AI, or Microsoft Foundry, where both data storage and processing can be pinned to a chosen region. UK and EU residency is part of that picture, with some country-level options continuing to expand through 2026, so confirm current region availability for your specific requirement rather than assuming it.

The honest summary is that the security work is real but bounded, and it is mostly your work, not the model's: least-privilege credentials, a clear record of what is connected, audit logging turned on, and a tested rule for what Claude is allowed to do without a human.

Indicative cost framing

There is no single MCP licence to buy. The cost of connecting Claude to your systems has three parts, and only the first has a published figure. The Claude Enterprise plan is priced per user per month, billed annually, with that seat fee covering access only; all usage is then billed separately at standard API rates based on what your teams actually consume. Anthropic does not publish a single per-seat figure and applies seat minimums, so treat the seat cost as a sales-quoted number rather than a fixed list price.

The second cost is integration effort: the work to stand up and govern each connection. For the managed Enterprise connectors to common workplace tools, that effort is low. For custom or remote MCP servers to your own line-of-business systems, it is a scoped engineering task. The third cost is the ongoing one that organisations underestimate: maintaining connections, reviewing access, and monitoring usage as your systems change. Budget for that as an operating cost, not a one-off.

We are not putting illustrative pound figures on the build here because they would be guesses. The defensible planning position is: a per-seat platform cost plus consumption, a per-connection build cost that scales with how bespoke the system is, and a standing operating cost for governance.

Where to start

The AI Consultancy scopes MCP rollouts connection by connection, lowest risk first. For the underlying delivery see our Claude implementation service, for help deciding which systems to connect first see our Claude consulting service, and for connecting Claude into your wider business processes see our workflow automation service.

Sources

• Anthropic, "Introducing the Model Context Protocol", 25 November 2024.
• Model Context Protocol documentation, "What is the Model Context Protocol (MCP)?", accessed June 2026.
• Anthropic, "Donating the Model Context Protocol and establishing the Agentic AI Foundation", 2025.
• Claude Help Center, "What is the Enterprise plan?", accessed June 2026 (managed connectors, SCIM, audit logs, customer-managed encryption keys, US-only inference, per-seat plus usage pricing).
• Claude, "Regional Compliance" (regional data residency and inference via AWS Bedrock, Google Cloud Vertex AI, and Microsoft Foundry; GDPR, SOC 2 Type 2, ISO 27001/27017/27018), accessed June 2026.