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Free Agent Skill Security Analyzer for Claude AI. Detect dangerous permissions, code execution vulnerabilities, and data leaks before deployment. Secure your AI agents today.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | dataprotocol.com | skillrisk.org |
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| Platforms | — | |
| Company | — | 1 - 9 employees · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of Data Protocol yet.
SkillRisk is a specialized security analysis tool designed for the AI Agent ecosystem, specifically focusing on Claude Code and Model Context Protocol (MCP) skills. As developers give AI agents more permissions (shell access, file manipulation), the risk of executing malicious code increases....
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Sven Mawson - Evolution of the Google Data Protocol
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As answered by people managing Data Protocol and SkillRisk.org.
SkillRisk.org's answer:
SkillRisk is the first dedicated security scanner built specifically for the Claude Code and Model Context Protocol (MCP) ecosystem. Unlike general-purpose code linters, SkillRisk understands agent-specific attack vectors—such as PreToolUse hook hijacking, implicit permission leaks in JSON/YAML definitions, and data exfiltration patterns in MCP server configurations. It brings "Static Application Security Testing" (SAST) to the world of AI Agents.
SkillRisk.org's answer:
Most traditional security tools audit application code but ignore the configuration layer of AI agents. You should choose SkillRisk because: Context-Aware: It detects risks specific to AI agents (e.g., giving an LLM rm -rf permissions) that standard linters miss. Pre-Runtime Safety: It allows you to audit third-party skills before you install them, preventing supply chain attacks. Privacy-First: Our "Local-First" architecture ensures your skill definitions are analyzed in-memory and never stored on our servers.
SkillRisk.org's answer:
Our primary audience includes AI Engineers, DevOps professionals, and software developers who are building autonomous agents using Claude Code or implementing MCP servers. It is a must-have tool for anyone integrating community-contributed skills or third-party tools into their agent's workflow.
SkillRisk.org's answer:
We built SkillRisk after realizing a terrifying gap in the AI workflow: developers scrutinize human code in Pull Requests but blindly copy-paste "Skills" that give AI agents shell access. After witnessing an incident where a malicious "Color Picker" skill silently exfiltrated credentials and caused $54,000 in cloud bills, we decided to build a "firewall" for AI skills. We treat Agent Skills as executable code that requires strict auditing.
SkillRisk.org's answer:
The platform utilizes a custom-built Static Analysis Engine specifically tuned for parsing JSON, YAML, and Markdown skill definitions. It employs strictly typed rule sets to detect logic vulnerabilities and permission scopes without executing the code. The web interface is designed for zero-persistence data processing to ensure maximum security.
SkillRisk.org's answer:
AI Engineers within the Anthropic developer community DevOps teams using Vercel Infrastructure developers at Nvidia Open source maintainers of MCP servers
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