MCP

The fastest interface to your partner program is the AI assistant you already use. Introw’s MCP server lets Claude, ChatGPT, Cursor, and other MCP clients securely read and act on your partner data, so you can ask questions and take action in plain language.

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What it does

MCP, the Model Context Protocol, is how AI clients connect to tools. Introw runs an OAuth-protected MCP server that exposes your partner program to AI clients. Once connected, an assistant can search partners, look up commissions and goals, review form submissions, prepare a business review, and take actions like updating a partner or creating a task, all scoped to your access. There is no separate dashboard to learn: you connect your AI client once through a secure sign-in, and your partner program becomes something you can query and act on conversationally. You can also extend MCP to your partners. With the partner MCP, each partner connects their own AI client and works with their own data, like their deals, commissions, and submissions, scoped to what they are allowed to see. That gives partners an AI assistant for the relationship, in the tools they already use.

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The problem it solves

Answers and actions that should take seconds get buried in screens and exports:

• Simple questions require digging through the app → Ask an AI client and get the answer in seconds.
• Routine updates interrupt real work → Assistants can update partners and create tasks on your behalf.
• Context lives in a tool you have to open → MCP brings partner data into the assistant you already use.
• Granting AI access feels risky → Connection is OAuth-protected and scoped to your own access.

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From problem to solution

Connect your AI client to Introw once over a secure OAuth sign-in. From then on, your partner program is available inside the assistant you already work in, for both questions and actions, without opening the app.

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Governance & the capability matrix

MCP access is not all-or-nothing. Every action an assistant can take runs through a vendor-configured capability matrix, and every action is scoped to the connected user’s own permissions.

• Permission-scoped reads - an assistant inherits the exact access the signed-in user already has, so it can never return data that user couldn’t see. A partner’s assistant reaches only that partner’s data.
• Per-action control - each MCP action is set to Read-only, Allowed, Approval Required, Write/Delete, or Blocked, so you decide which actions auto-execute and which require a human in the loop.
• Auditable by design - every read, write, and command is logged and, where it changes data, written back to the CRM system of record.

See Governance & trust for the full capability-matrix model, and Access & Security for the roles and permissions reads are scoped to.

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Use cases

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Impact

• AI-native - Your program is usable from the assistants your team already runs.
• Work where you already are - Questions and actions happen in the AI client, not the app.

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Who it’s for

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Works with

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Headless

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Going deeper