Modellkontextprotokoll

Das Model Context Protocol (MCP) ist ein offener Standard, der es KI-Modellen ermöglicht, über eine einheitliche Schnittstelle mit externen Datenquellen und Tools zu kommunizieren. Wir führen Benchmarks und Vergleiche verschiedener MCPs durch, um deren Leistungsfähigkeit, Zuverlässigkeit und Funktionalität zu bewerten.

AI-Toolzugriff mit dem MCP Gateway zentralisieren

ModellkontextprotokollMai 26

We’ll walk through the evolution of AI tool integration, explain what the Model Context Protocol (MCP) is, and show why MCP alone isn’t production-ready. Then we’ll explore real-world gateway implementations for connecting AI agents to external tools. OpenAI-compatible and lightweight MCP Gateways Designed to make MCP tools easily accessible to agents and AI clients.

ModellkontextprotokollApr 24

MCP Benchmark: Top MCP Server für den Webzugriff

We benchmarked 8 MCP servers across web search and extraction, as well as browser automation tasks, by running 4 different tasks 5 times on all suitable MCPs. We also performed a load test involving 250 concurrent AI agents.

ModellkontextprotokollMär 6

AI Apps mit MCP Memory Benchmark & Tutorial

We tested four Model Context Protocol (MCP) memory servers to measure which ones actually retain and retrieve context across AI agent sessions. Using LangChain’s ReAct Agent, we connected each server, ran standardized multi-session conversations, and scored them on memory operation accuracy.

ModellkontextprotokollJan 28

Code-Ausführung mit MCP: Ein neuer Ansatz für die Effizienz von KI-Agenten

Anthropic introduced a method in which AI agents interact with Model Context Protocol (MCP) servers by writing executable code rather than making direct calls to tools. The agent treats tools as files on a computer, finds what it needs, and uses them directly with code, so intermediate data doesn’t have to pass through the model’s memory.