In the Model Context Protocol (MCP), the server is the side that exposes tools, data sources, and functions that an AI model can use. It defines what actions are available—such as retrieving data, writing files, running a query, or calling an external API—and enforces strict rules about how these actions can be performed. The server controls permissions, input/output formats, and security boundaries.
Developers build MCP servers to connect AI models with their systems. For example, an MCP server could expose access to a database, an internal application, a financial API, or a workflow engine. Because the protocol is standardized, these servers work across different AI models without needing custom integration for each one.
The server ensures that AI interactions remain predictable and safe. Every tool exposed through the server has defined behavior, limited access, and clear constraints. This allows organizations to connect AI to real business systems while maintaining control over what the model can do.
An MCP server acts as the secure gateway between AI and external systems. It allows AI tools to be powerful without sacrificing safety, transparency, or control.
The server advertises its available tools—such as “query database,” “fetch stock data,” or “create file”—and the AI model can call these tools when needed. Each tool has structured inputs and outputs, so the AI knows exactly how to use it. The server processes the request, enforces permissions, and returns results in a consistent format.
Developers can link almost any data source or service, including databases, APIs, file storage, CRM systems, research tools, or internal apps. If it can be accessed programmatically, it can be added to an MCP server. This allows teams to build AI assistants that work with their real data while controlling every action.
Traditional AI integrations often give broad or unclear access, which can lead to data leaks or unauthorized actions. An MCP server enforces strict permissions and tool boundaries. The AI can only perform the actions explicitly exposed by the server, and all interactions are logged. This improves transparency, safety, and compliance.
A fintech company builds an MCP server that exposes only two secure tools: “Get historical price data” and “Generate PDF report.” The AI assistant can use these tools to run analysis and create reports, but cannot access any other files or systems.
An MCP server can provide controlled access to FinFeedAPI’s APIs: Stock API, Currencies API, SEC API, Flat Files S3 API and Prediction Markets API, enabling AI assistants to retrieve financial data securely while ensuring all actions follow strict permissions and organizational rules.
