How You Can Benefit From MCP - Business AI’s New Standard

From legal to finance, everyone’s asking tools like ChatGPT and Claude to summarise, draft or analyse.

But most of that work still happens in isolation: an assistant gives you an answer - then you manually copy it into Slack, Salesforce or your CLM. Nothing actually connects.

That’s the gap the Model Context Protocol (MCP) closes.

What does MCP do?

The Model Context Protocol is an open standard that lets AI assistants work directly inside your business systems, securely and with full governance.

Instead of one-off integrations or risky data pastes, MCP gives large language models (LLMs) like Claude and ChatGPT a safe, structured way to talk to enterprise apps such as Salesforce, Google Drive, SharePoint or Concord via published MCP servers.

With MCP, you can tell ChatGPT something like:

“Find vendor agreements expiring next quarter in Concord, and post a summary in our #renewals Slack channel.”

And your AI will actually execute those actions in your software - finding the requested contracts in Concord, then posting the summary in your Slack channel.

No exports. No unmanaged plug-ins. No need to click away from ChatGPT at all.

In short, MCP works like a universal “USB adapter” for thousands of software tools - providing AI with plug-and-play access to real functionality, through just a few minutes of setup.

How does MCP make this possible?

Ever since Anthropic published the MCP specification in 2024, adoption has skyrocketed. Thousands of leading companies - including Microsoft, Google, HubSpot, Salesforce, Slack, Jira and Concord - have now adopted the MCP standard.

Setup for the end user is quick and easy - and free! Just search for your favorite software’s MCP server, and click to enable the connection in ChatGPT, Claude or your LLM of choice.

Once your AI assistant has confirmed the connection, you’ll be able to execute actions in the external app, simply by telling your AI what to do.

If you’re familiar with application program interfaces (APIs), you may be wondering if MCP is related. And the answer is yes! MCP servers act as wrappers around APIs, making it easier for LLMs to know how to interact with third-party apps effectively.

Each app’s MCP server tells LLMs what resources are available in that app, which actions the app can perform and how to submit requests to that app - enabling your AI assistant to read and write data, and perform other actions, in external apps (with your permission, of course).

In short, APIs made systems programmable. MCP makes them conversationally programmable - and safe enough for enterprise scale.

For Legal, IT, Finance and HR, MCP turns your AI assistant into the interface layer for third-party software you already use, rather than another silo.

How to get started with MCP 

1. Inventory live data sources. Check whether your core systems have MCP servers or SDKs (start with the GitHub).
   
   
2. Authenticate once via your enterprise SSO and align scopes with OAuth 2.1.
   
   
3. Pilot one workflow. Example: connect your CLM’s MCP server and ask, “Summarise supplier contracts expiring in Q1,” then post to Slack.
   
   
4. Scale safely. Add connections incrementally; governance and audit follow the same patterns across servers.

The bottom line

MCP turns AI from a chat window into an operational layer.

It’s the framework that lets assistants work inside your systems - securely, contextually and in real time.

If you already use AI but still shuffle data between apps, MCP is the step that removes the friction, without removing the guardrails.

Learn more at Concord's Model Context Protocol (MCP) page.