What Is Model Context Protocol (MCP)?

What Is MCP?

MCP is a shared way for an AI assistant to ask another system for information or to take an action there. The official introduction compares it to a USB-C port: one standard plug instead of a different cable for every device.

Anthropic released the protocol as open source in November 2024, describing it in its announcement as a standard for connecting assistants to the systems where data lives. It has since been adopted by other AI applications, which is why it now appears in software vendor roadmaps and contracts.

For a buyer, MCP is less about code and more about reach. It decides whether the AI tools your team already uses can read from and work inside the software you rent.

What Is an MCP Server?

An MCP server is the piece a software product publishes so AI applications can use it. It lists a set of tools, such as search records or create a ticket, and describes what each one needs and returns.

A remote MCP server runs on the vendor's side and is reached over the internet, usually behind a sign-in. A local server runs on the user's own computer, which is common for developer tools that work with files.

HissingKitty publishes its own public server so assistants can look up company pricing, alternatives and buyer reviews. The Developers page shows how to connect it and which questions it answers.

How Do MCP Clients and Servers Work Together?

The client is the AI application, such as Claude, ChatGPT or a coding assistant. The server is the outside system. The client asks the server what tools it offers, then calls them while answering a person's request.

• Discovery: the client reads the server's list of tools and their descriptions.
• Calls: the model picks a tool, sends inputs, and gets structured results back.
• Permission: the person signs in to the server, and the server only returns what that account is allowed to see.

Because the format is shared, one server works with many clients. That is the main difference from older integrations, where each AI product needed its own connector for each vendor.

Why It Matters to Software Buyers

If your team moves daily work into AI assistants, a system that cannot be reached from them becomes harder to use and easier to replace. MCP support is turning into a practical question at renewal, next to single sign-on and data export.

It also changes switching costs. When an assistant can read and write records in several systems, the interface you pay for matters less, and a smaller or AI-native tool can sit alongside an established one.

Ask each vendor whether it offers an MCP server, which plan includes it, and whether it can write data or only read it. Note the answer in your renewal file so the next review starts with facts.

How It Shows Up in Practice

HubSpot documents a remote MCP server on its developer site that gives compatible AI tools read and write access to CRM data such as contacts and deals. A sales team can ask an assistant to summarize open deals without exporting a report.

Atlassian publishes an MCP server that connects agents to Jira and Confluence work. A support lead can ask for open tickets on one customer and link them to a project page in the same request.

In both cases the subscription still applies. MCP gives the assistant a door into the product; it does not replace the product's data, permissions or pricing.

Is MCP Secure?

The protocol itself is a format, so safety depends on how each server and client is set up. The main risks are giving an assistant broader access than the person needs and connecting servers nobody has checked.

• Prefer servers published by the vendor itself, signed in with your normal account.
• Start with read-only access and add write actions only where a person reviews them.
• Review which connected servers each team uses, the same way you review shadow IT.

Treat a new server like a new vendor integration. Confirm who runs it, what data it can reach, and how access is removed.

What Should You Do Next?

List the five tools your team pays the most for and check which publish an MCP server. A spend audit gives you that list with bills attached.

For workflows where no server exists, compare paying for an add-on with a small custom connector in the Build vs. Buy Calculator. Estimates there follow our methodology.

If you only need to ask questions of your data, read MCP vs. API first; an existing API may already be enough.