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 API 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 encodes messages using JSON-RPC 2.0 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.

Related Resources

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:

• Build a Python MCP Client to Test Servers From Your Terminal (Tutorial)
• Python MCP Server: Connect LLMs to Your Data (Quiz)
• Build a Python MCP Client to Test Servers From Your Terminal (Quiz)