What Is MCP Connector?

What Is an MCP Connector?

A connector is what a person adds inside an AI application to reach another product. Behind it sits an MCP server run by that product or a third party.

The word comes mostly from Claude. Its help article on custom connectors explains that you can connect Claude to existing remote MCP servers or build your own.

Other AI applications use different names for the same idea. What matters is that the connection uses MCP, so the same server works across them.

What Are Claude Connectors?

Claude connectors are MCP servers added to Claude, either from Anthropic's directory or as custom connectors by address. Claude's help article says custom connectors are available across its plans, with Free users limited to one.

Directory listings have been reviewed by Anthropic. Custom connectors have not, and Claude's own guidance warns about connecting services it has not verified.

HissingKitty is listed in the Claude directory, so buyers can ask Claude about software prices and alternatives with sourced answers. Setup steps for other assistants are on the Developers page.

How Do You Add a Connector?

• Open the AI application's connector or integration settings.
• Pick the service from the directory, or paste the address of its remote MCP server.
• Sign in with your normal account for that service and approve the access it asks for.
• Ask a test question and check the answer against the service itself.

Most remote connectors need no code. Local ones, common for developer tools, are installed on a computer instead.

Why It Matters to Software Buyers

Connectors move work out of the vendor's screen and into the assistant. If most daily use happens there, you may be paying for seats and features people no longer open.

That is useful at renewal. Check how many people still log in to the product directly and whether a lower plan covers what the connector uses, then compare against AI-native software that was built for this kind of use.

It also helps with switching costs. When an assistant reaches your data through a standard connector, moving one system behind it disrupts less of the daily workflow.

How It Shows Up in Practice

A sales team adds the HubSpot connector so reps can ask Claude for deal summaries. HubSpot documents read and write CRM access on its MCP page.

A product team adds the Atlassian connector to pull Jira issues and Confluence pages into one answer. The subscription and its permissions stay exactly as they were.

A buyer researching a renewal adds HissingKitty and asks what teams report paying for a tool and which alternatives exist.

What Are the Risks?

A connector can act with your account's permissions, so broad access means broad reach. Start with read-only actions where the application allows it.

Unverified servers are the larger risk. Prefer connectors run by the vendor itself or reviewed in a directory, and keep a list of who uses which, as you would for shadow IT.

Remove connectors when people change roles or leave. Signing out of the service usually ends the connection.

MCP Connector vs. Built-In AI Add-On

Many vendors now sell their own AI assistant as a paid add-on inside the product. A connector takes the other route: your existing AI application reaches the product's data instead.

The add-on keeps you in one vendor's screen and pricing. The connector lets one assistant work across several tools, which can make a separate add-on per product unnecessary.

Before buying an add-on at renewal, check whether the vendor offers a connector on your current plan, and test whether it covers the questions your team actually asks.

What Should You Do Next?

Run a spend audit to see your largest bills, then check which of those tools offer a connector. Where none exists, the Build vs. Buy Calculator helps you weigh a small custom one, and MCP vs. API explains when an API alone is enough.