An AI assistant is only as useful as what it can see and do. Ask it "which customers haven't paid this month?" and it can't answer unless it can reach your records.
For a long time every AI tool needed its own custom connection to every system. The **Model Context Protocol (MCP)** fixes that. It's an open standard, introduced by Anthropic in late 2024 and since adopted widely across the AI industry, for connecting AI assistants to tools and data. Interest is high enough that Nairobi is hosting an MCP Dev Summit on 19–20 November 2026.
MCP in one sentence
MCP is like a USB-C port for AI: build one connector for your system, and any MCP-compatible AI assistant can plug into it.
How it works
- MCP server: a small program that sits in front of one of your systems (a database, CRM, file store, internal API) and describes what the AI may do there, e.g. "look up an order" or "list unpaid invoices".
- MCP client: the AI app or agent (a desktop assistant, coding tool or your own chatbot) that connects to servers and uses those actions.
- The model decides when to call an action, reads the result, and uses it in its answer or next step.
Why businesses should care
- Build once, use everywhere: one MCP server for your system works with many AI tools, including ones that don't exist yet.
- You control access: the server only exposes the actions you choose, so the AI can read orders without being able to delete them.
- Less lock-in: switching AI provider doesn't mean rebuilding every integration.
- Ready-made connectors: MCP servers already exist for many popular tools, so you only build what's unique to you.
Practical examples
| Your system | What an MCP server could let AI do |
|---|---|
| Point of sale | Report yesterday's sales and low-stock items |
| CRM | Find leads not contacted in 7 days and draft follow-ups |
| Accounting | List overdue invoices and prepare reminders for approval |
| Support inbox | Search past tickets to answer a customer's question |
| Internal documents | Answer staff questions from your policies and manuals |
Security: the part not to skip
- Least privilege: start with read-only actions; add write actions one at a time.
- Require approval for anything that sends money, emails customers or deletes data.
- Authenticate every connection and keep secrets out of prompts and code.
- Log every action the AI takes, so you can review what happened.
- Watch for prompt injection: text inside documents or emails can try to trick an AI into misusing tools. Limits and approvals are your safety net.
- Only install MCP servers from sources you trust, and review what they can access.
Do you need MCP?
- Probably yes if you want AI assistants or agents working with your own systems and data, or you use more than one AI tool.
- Probably not yet if you only use AI for writing and brainstorming.
- Definitely if you're a software company: offering an MCP server lets your customers' AI tools use your product.
MCP is quietly becoming the standard way AI gets work done inside real businesses. Building a careful, permission-limited MCP server for your key system is one of the highest-value AI projects you can do right now. We design and build MCP servers, AI agents and integrations for businesses in Kenya and worldwide, with security and approvals built in.
See our AI automation service, hire our developers, or read AI agents for small business.
