MCPBench: The evaluation benchmark on MCP servers

by modelscope · MCP Server · ★ 252

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 67/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

benchmarkdatabasemcpmcp-serverwebsearch

Quick Facts

Stars252
Forks17
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score67/100
Open Issues6
Last Updated2025-09-03
Created2025-04-13
Platformsbrowser, mcp, python
Est. Tokens~6634k

About MCPBench

🦊 MCPBench: A Benchmark for Evaluating MCP Servers [![Documentation][docs-image]][docs-url] [![Package License][package-license-image]][package-license-url] 中文 | English MCPBench is an evaluation framework for MCP Servers. It supports the evaluation of three types of servers: Web Search, Database Query and GAIA, and is compatible with both local and remote MCP Servers.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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