Agentic AI Model Context ProtocolModel Context Protocol

Model Context Protocol

Model Context Protocol (MCP) is an open standard that lets AI models connect to external data sources and tools through a unified interface. We benchmark and compare various MCPs to evaluate their performance, reliability, and capabilities.

Code Execution with MCP: A New Approach to AI Agent Efficiency

Benchmark

Aug 27

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…

Model Context Protocol

Benchmark

Aug 24

MCP Gateway Benchmark: Latency & Security of 6 Gateways

An MCP gateway sits between an AI agent and the tools it calls, and vendors position it as the security layer for that traffic. We benchmarked six MCP gateways against one instrumented backend on a single box, measuring added latency, per-tool authorization, content protection, and audit completeness. A product appears against a control only if…

Model Context Protocol

Benchmark

Aug 21

MCP Benchmark: Top MCP Servers for Web Access

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. *Web search & extraction tasks are run with Bright Data’s default MCP server, browser automation tasks are…