What Is an MCP Connector? How AI Chat Uses Your Other Apps

MCP stands for Model Context Protocol. It is an open standard for how an AI assistant talks to outside apps and data. An app that supports it runs an MCP server: a web address the AI can contact to find out what the app can do. A connector is the saved link between your AI assistant and that server, usually with your sign-in or key attached.

Once a connector is in place, the AI does not just know about the app, it can use it. The server hands the AI a list of tools, each with a name and a short description, such as search contacts, read a page, list files or create a draft. When you ask a question that needs one of those tools, the AI calls it, reads the result and uses it in its reply.

People also call this an MCP plugin or an MCP integration. The words differ by app, but the idea is the same: one standard way to plug an AI assistant into the tools you already use, instead of a custom integration for every pair of apps.

Every MCP connector follows the same basic flow, whichever AI app you use:

1. Connect: you add the app, either from a list or by pasting its MCP server address. You sign in to the app in its own window, or paste an API key or token.
2. Discover: the AI asks the server which tools it offers and reads their names and descriptions.
3. Ask: you type a normal request, for example, Find the deals in my CRM that closed last month.
4. Call: the AI decides which tool fits, calls it, and gets the data back.
5. Answer: the AI writes a reply that uses your real data, or reports what it did in the other app.

The important point is that you do not pick the tool yourself. You describe the job in plain words, and the AI chooses from the tools each connector exposes. That is also why trust matters: the AI can use any tool a connector gives it while it works on your request.

An API is the raw way two programs talk, and someone has to write code against it. An MCP connector wraps an app's abilities as named tools that an AI assistant can read and call without new code for each app. Many MCP servers are built on top of the app's API.

An older style AI plugin was usually built for one AI app only. An MCP server follows a shared standard, so the same server can work with different AI apps that support MCP.

An automation tool runs fixed steps when a trigger fires, for example, when a form is filled in, add a row to a sheet. That is better when you want the same thing to happen every time with no one watching. An MCP connector is better when the request changes each time and you want the AI to decide what to look up. The two can work together: some automation tools offer their own MCP server, so an AI can start their workflows.

Say you run marketing for a small software company. Your leads live in a CRM, your campaign notes live in a notes app, and your team talks in a chat app.

Without connectors, you export the leads, copy the notes and paste both into an AI chat, then copy the summary back out. With connectors for the CRM and the notes app, you type one request: Read last week's campaign notes, check how many new leads came from that campaign in the CRM, and write a five line summary for the team.

The AI calls the notes tool to read the page, calls the CRM tool to search the leads, and writes the summary from both. If you also connected the chat app and it exposes a send message tool, you could ask it to post the summary for you.

Check the first few results by hand. A connector gives the AI your real data, but the AI still decides which tool to call and how to read the result, so make sure it searched the right list and the right dates before you rely on it.

A connector can read and sometimes change data in another app, so treat it like giving an assistant a key:

• Only connect apps and MCP servers you trust. An unknown server can offer tools that do more than their names suggest.
• Use sign-in with approval where the app offers it, so you can see what access you are granting and revoke it later in that app.
• If you paste an API key, give it only the access the job needs, when the app lets you choose.
• Pause a connector you are not using. You can switch it back on when you need it.
• Look at the list of tools a connector exposes before you rely on it, so you know what the AI is able to do.
• Check any action that sends, deletes or changes something before you ask the AI to do it in bulk.

In Infinall AI, a connector links Infinall Chat to another app, so chat can use your real data and take actions in that app. Open Settings, then Connectors. The same list is in chat under Customize.

To connect an app from the directory:

1. Click the Browse tab. Type a name in Search apps, or click a category chip.
2. Click Connect on the app.
3. If the window says Sign in to the app, click it, sign in there and approve access. Infinall never sees your password. If it asks for a key, paste it and click Connect.
4. You land on the Connected tab with the number of tools the app gave Infinall.

The featured list includes HubSpot, Apollo.io, Klaviyo, Semrush, Similarweb, Canva, Figma, Notion, Webflow, Shopify, Stripe, Zapier, Make, Airtable, Slack, Gmail, Google Drive, Google Sheets and Asana, and the full directory has thousands more.

To add any other MCP server, click Custom, type a Name, paste the address in MCP server URL (it must start with https://), add a token in Access token (optional) if the server needs one, and click Connect. Switch off Use (app name) to pause a connector, or click Remove (app name) to delete it.

Limits to know: Infinall reads at most 40 tools from each connector, the directory loads 60 apps at a time, a connector name is cut to 80 characters, a sign-in link lasts 15 minutes, and one connector result is cut off at 30000 characters.

Connecting, pausing and removing apps is free and uses no credits, on Free and Pro alike. Chat replies that use a connector follow the normal chat cost. The free plan gives 1,000 credits every month with no card, and one credit is one US cent. Pro is $10 for the first month, then $30 a month or $299 a year, with 3,000 credits a month (India: Rs 999 first month, then Rs 2,899 a month or Rs 33,999 a year).