Model Context Protocol (MCP)

Model Context Protocol (MCP) is an open, client-server communication standard that lets AI applications connect to external tools, resources, and predefined prompts through a consistent interface.

MCP defines how a client discovers and invokes server-provided capabilities:

  • Tools are callable actions or APIs requests that the client can ask the server to perform.
  • Resources are structured data or context, such as files, database tables, documents, and schemas, accessible by URI, which the client or model can reference.
  • Prompts are predefined prompt templates that clients can fetch, fill with arguments, and execute to drive structured interactions with language models.

MCP can encode messages using JSON over standard transports such as standard input/output (stdio) or streamable HTTP.

The goal is interoperability and portability across assistants, hosts, and integrations, so developers can build a connector once and reuse it in many AI apps.

Python MCP: Connect Your LLM With the World

Tutorial

Python MCP Server: Connect LLMs to Your Data

Learn how to build a Model Context Protocol (MCP) server in Python. Connect tools, prompts, and data to AI agents like Cursor for smarter assistants.

intermediate ai

For additional information on related topics, take a look at the following resources:

By Leodanis Pozo Ramos • Updated Oct. 25, 2025
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