MCP server for authenticated customers to access and operate the product's core functionality, including account management, service operations, and real-time analytics.
Give your Ai agent access to a collection of tools via MCP's standardized format.
Retrieve details about the customer's account, including subscription information, usage statistics, and service status.
Allow authenticated customers to update their account preferences and settings.
Fetch real-time data and analytics from core service modules for the authenticated customer.
Initiate key product operations on behalf of the customer.
Core Product MCP leverages the Model Context Protocol to provide authenticated customers with secure access to our product's key features as if they were using the product directly. This MCP enables agents that customers use the ability to manage their account details, monitor product data within their account, and initiate core operations through a set of dedicated tools.
The available tools include get_account_overview, which delivers a detailed snapshot of account health and subscription data; update_account_settings, which facilitates changes to user preferences; fetch_service_data, which retrieves live analytics and performance metrics; and trigger_service_action_x, which supports execution of critical operational tasks.
By integrating these functionalities, the Core Product MCP empowers customers to leverage our product’s capabilities ands integrate it will other activties they are doing with their ai tools.
Ai builders can use existing MCPs to give their agents access to external tools and resources. They can also build their own MCPs to give their agents - and optionally others - access to internal tools and resources.
A third-party MCP server is provided by an external developer that exposes the functionality of services or tools created by orgas outside of your organization—such as Airtable, Perplexity, Postgres or similar—through the MCP standard.
Using a third-party MCP server within agents that you build means that your agents are immediately empowered with access to these external services—with minimal development and maintainence of custom integrations.
Typically, this means that your company authorizes agents that you build to interact with your organization's accounts on these platforms (for example, your company's Airtable account, or your company's data stored in Postgres databases) rather than your end users' accounts.
Another use for these 3rd-party MCP servers may be that your team members add them to MCP client apps like Anthropic's Claude general AI app or the Cursor coding app.
You want inspiration for ways your team can add capabilities and tools to your go-to-market Ai agents.
You want inspiration for ways to add capabilities and tools to your Ai agents.
You want inspiration for ways your team can add capabilities and tools to the Ai agents that affect the stage of the customer journey you're focused on.
Model Context Protocol (MCP) is an open standard for giving Ai such as LLMs access to external tools and resources. It allows developers to create reusable, interoperable components that can be used across different AI applications and agents.
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