MCP server to generate images using Amazon Nova Canvas via text prompts and color guidance.
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.
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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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