MCP (Model Context Protocol) is an open standard that lets AI agents discover and use external tools in a consistent way. Introduced by Anthropic in 2024, it gives AI assistants like Claude or ChatGPT one shared way to ask a system "what can I do here?" and then carry out one of those actions, instead of needing a custom-built connection for every tool.
What MCP does and does not do
Before MCP, connecting an AI assistant to a business system meant building a one-off integration for that specific assistant and that specific system. MCP replaces that with a shared format. A system publishes its available actions through an MCP server: what each action is called, what input it needs and what it returns. Any AI agent that supports MCP can read that list and use it.
What MCP does not do is the work behind the action. The protocol defines how the agent asks and how the answer comes back. It does not store the credentials for your ERP, it does not know how your webshop's order format maps to your bookkeeping, and it does not retry a failed sync or keep a record of who did what. It assumes something underneath takes care of that.
MCP vs. iPaaS
| MCP | iPaaS | |
|---|---|---|
| What it is | A protocol - a standard way for AI agents to find and call tools | A platform that runs integrations between systems |
| Who uses it | AI agents and assistants | Systems, scheduled workflows and the people who manage them |
| What it handles | Which actions exist, and the request and response for each | Credentials, data mapping, multi-step flows, retries and logs |
| When it runs | When an agent triggers an action, in real time | Continuously - scheduled syncs, webhooks and background jobs |
| Best for | Letting an AI agent ask questions and take specific actions | Moving correct data between systems, reliably, every time |
Does MCP replace an iPaaS?
MCP and an iPaaS do two different jobs. MCP gives an AI agent a standard way to reach your systems. An iPaaS makes sure the data the agent finds there is correct, consistent and up to date - and an agent can only be as reliable as that data.
In e-commerce, most integration work happens without any agent involved. Orders flow from the webshop to the ERP, stock levels sync back, and payouts from the payment provider are reconciled against orders. That runs on a schedule, thousands of times a day, and it has to be predictable. MCP does not change any of it.
What MCP adds is a second way in. When someone asks an AI agent "why hasn't order 10432 reached Fortnox?", the agent calls an action through MCP, and the integration platform does the actual work: finding the order, checking its sync status and reading the error.
The mapping logic stays in the integration too. MCP has no idea that a Swedish VAT account like 2611 may need to become 2641 in another system, depending on VAT rate and transaction type. That knowledge lives in the integration layer, which is why an agent connected straight to raw systems acts on data it cannot interpret correctly.
So the real question is not MCP or iPaaS. It is whether your integration platform supports MCP, so AI agents can use the connections you already rely on.
Scoped, approved actions: what this means in practice
An MCP server does not give an AI agent a login to your systems. It gives the agent a list of specific actions, and what it may use is decided on the platform side, not by the agent. With Junipeer, that's set by the level of the API key you create for the agent.
For an e-commerce integration, that can look like this.
With a read-only key, an agent can:
- Check the sync status of an order
- Look up a payout and the orders it covers
- Read the error message behind a failed transfer
- Explain what a setting does and what it's set to
With a higher key level, an agent can also:
- Re-run a sync that failed
- Change settings, mappings and schedules
- Write data to connected systems
An agent never:
- Sees the credentials for your ERP or other systems
- Goes beyond what its key allows
Settings changed through MCP are recorded in the integration's change history, marked with the key that was used, so you can see what changed and when. Junipeer's MCP server itself keeps no copy of your requests.
MCP at Junipeer
Junipeer's MCP is available now, in two forms. Workspace MCP (€49/mo per workspace) lets AI agents like Claude or ChatGPT check, explain and fix your integrations. A System MCP (from €39/mo) connects an AI agent to one system's data, such as Fortnox, Klarna or Magento. See all systems with MCP. Both run on the same platform and connections that already handle your orders, payouts and bookkeeping.
It's the Expose part of Junipeer AI, alongside Build (tools for building connections) and Run (Ask Junipeer AI, which diagnoses integration errors).