{"repo":"Accenture/mcp-bench","free":true,"listed":false,"github":"https://github.com/Accenture/mcp-bench","clone":"git clone https://github.com/Accenture/mcp-bench.git","description":"MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers","language":"Python","stars":502,"topics":[],"license":null,"category":"mcp-servers","readme_excerpt":"MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers Overview MCP-Bench is a comprehensive evaluation framework designed to assess Large Language Models' (LLMs) capabilities in tool-use scenarios through the Model Context Protocol (MCP). This benchmark provides an end-to-end pipeline for evaluating how effectively different LLMs can discover, select, and utilize tools to solve real-world tasks. News [2025-09] MCP-Bench is accepted to NeurIPS 2025 Workshop on Scaling Environments for Agents. Leaderboard Rank Model Overall Score ------ ------- --------------- 1 gpt-5 0.749 2 o3 0.715 3 gpt-oss-120b 0.692 4 gemini-2.5-pro 0.690 5 claude-sonnet-4 0.681 6 qwen3-235b-a22b-2507 0.678 7 glm-4.5 0.668 8 gpt-oss-20b 0.654 9 kimi-k2 0.629 10 qwen3-30b-a3b-instruct-2507 0.627 11 gemini-2.5-flash-lite 0.598 12 gpt-4o 0.595 13 gemma-3-27b-it 0.582 14 llama-3-3-70b-instruct 0.558 15 gpt-4o-mini 0.557 16 mistral-small-2503 0.530 17 llama-3-1-70b-instruct 0.510 18 nova-micro-v1 0.508 19 llama-3-2-90b-vision-instruct 0.495 20 llama-3-1-8b-instruct 0.428 Overall Score represents the average performance across all evaluation dimensions including rule-based schema understanding, LLM-judged (o4-mini as judge model) task completion, tool usage, and planning effectiveness. Scores are averaged across single-server and multi-server settings. Quick Start Installation 1. Clone the repository 2. Install dependencies 3. Set up environment variables 4. Configure MCP S","default_branch":null,"files":null,"tree":[],"storefront":"/r/Accenture","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Accenture/mcp-bench/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}