Anthropic’s Model Context Protocol (MCP): A Developer’s Guide to Long-Context LLM Integration

Large language models (LLMs) now boast massive context windows allowing them to process entire documents. However, effectively providing relevant context to these LLMs is still a challenge. Developers traditionally use complex prompt engineering or retrieval pipelines for this. Anthropic's Model Context Protocol (MCP) offers a new open standard to simplify and standardize context provision. MCP acts as a universal connector, enabling LLMs to seamlessly access external data, tools, and systems. This protocol standardizes how AI applications provide context to LLMs using a client-server architecture. It connects AI assistants to various data sources like files, databases, and cloud services. Before MCP, integrating LLMs with new data sources required custom connectors for each case. MCP simplifies this by providing a universal interface. This reduces the need for numerous bespoke implementations, making integration more efficient.