What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open standard that defines how AI assistants and agents connect to external tools and data sources. Instead of building a custom integration for every combination of AI app and software product, a developer builds one MCP server that any AI app with MCP support can use.
Anthropic introduced MCP in November 2024. Other AI companies, including OpenAI and Google, have since added support, which has made it a widely used way to link AI models to business software.
MCP has two sides. An MCP server exposes data and actions from a system, such as a CRM, a file store or an analytics platform. An MCP client, built into an AI app, discovers those capabilities and lets the model use them when a user asks for something. The model can then fetch live data or trigger an action instead of relying only on its training data. That is a form of grounding: the answer rests on current information.
Why MCP matters for marketing and AI visibility
For marketing teams, MCP means you no longer have to paste data into a chat window. An assistant connected to your analytics, CMS or monitoring tools can answer questions such as "which prompts did we lose visibility on this week?" with real numbers and pass them to the next step of a workflow.
MCP is also a building block for AI agents. Agents use it to reach tools and data on their own, and some companies make parts of their product or catalog available through MCP servers. As more tasks run through AI assistants, being reachable through standard connections becomes part of being visible to them.
How to use MCP in your workflow
List the questions your team answers again and again with data from several tools.
Check which of those tools offer an MCP server and which AI assistants in your team support MCP.
Connect them with limited permissions first: read-only access, one workspace, one test user.
Write a few standard requests, such as a weekly visibility summary or a competitor check, and review the output before you automate anything.
Treat an MCP connection like any other integration: use trusted servers and grant no more access than needed. Trackbase offers an MCP connection that plugs your AI visibility data into your AI workflows, so you can ask about mentions, citations and competitors in an assistant that supports MCP.
Examples of MCP
A content team connects its CMS through MCP and asks the assistant to list pages that have not been updated in a year.
The sales team of a B2B software vendor lets an assistant pull account history from the CRM before each call.
An agency connects its AI visibility data and asks for a draft client report comparing this month's share of voice with last month's.
A webshop makes product availability accessible through an MCP server, so AI agents can check stock before recommending an item.
Frequently asked questions
Who created the Model Context Protocol?
Anthropic, the company behind Claude, introduced MCP as an open standard in November 2024. The specification is public, so anyone can build MCP servers or clients. OpenAI, Google and other AI companies have since added support, which is why the same MCP server can work with several AI assistants.
Is MCP safe to use with company data?
MCP itself is a protocol, so safety depends on how you use it. An MCP server can read data and sometimes take actions. Only connect servers from providers you trust, grant the smallest permissions that work and check what each tool is allowed to do. Treat a new MCP connection like any other software integration that touches company data.
Do I need to be a developer to use MCP?
Not always. Several AI assistants let you add a ready-made MCP server through their settings, and a growing number of software vendors offer one with setup instructions. Building your own MCP server does require development work. For most marketing teams, the practical route is connecting existing servers from tools they already use.