by illiahaidar · MCP Server · ★ 168
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcptrustchecker safe to install? View the security audit →
🛡️ MCP Trust Checker The local-first, deterministic security scanner for MCP servers Know whether a Model Context Protocol server is safe before you connect it to your data. Zero install? Run the same deterministic engine as a free public web API → mcptrustchecker.com/api · offline · deterministic · no account · OAuth browser login for protected servers · reads the real published n
| Stars | 168 |
| Forks | 5 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.9762651172401/100 |
| Last Updated | 2026-07-26 |
| Created | 2026-07-13 |
| Platforms | mcp, node |
| Est. Tokens | ~20k |
These tools work well together with mcptrustchecker for enhanced workflows:
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mcptrustchecker is Security scanner for MCP (Model Context Protocol) servers — reads the real published npm/PyPI source, not just metadata, to catch tool poisoning, prompt injection, toxic flows & supply-chain risk. Off. It is categorized as a MCP Server with 168 GitHub stars.
mcptrustchecker is primarily written in TypeScript. It covers topics such as ai, artificial-intelligence, mcp.
You can find installation instructions and usage details in the mcptrustchecker GitHub repository at github.com/illiahaidar/mcptrustchecker. The project has 168 stars and 5 forks, indicating an active community.
mcptrustchecker is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mcptrustchecker on Agent Skills Hub include hasmcp-ce, tunnel-client, golf. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: