Model Context Protocol (MCP) has quickly become the standard protocol for federating tool calls between agents. Enterprises are starting to adopt MCP as a type of microservice architecture for teams to reuse each other's tools across different AI applications.
But there are real risks with using MCP tools in production agents. Tool names, descriptions, and argument schemas become part of your agent's prompt and can change unexpectedly without warning. This can lead to security, cost, and quality issues, even when the upstream MCP server hasn't been compromised or isn't intentionally malicious.
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But there are real risks with using MCP tools in production agents. Tool names, descriptions, and argument schemas become part of your agent's prompt and can change unexpectedly without warning. This can lead to security, cost, and quality issues, even when the upstream MCP server hasn't been compromised or isn't intentionally malicious.
We built
mcp-to-ai-sdk to prevent this. It's a CLI that generates static AI SDK tools from any MCP server, eliminating the issues that come from merging dynamic MCP tool definitions into agent loops.Read more
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