No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by sdras · MCP Server · ★ 125
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is jev-webmcp-extension safe to install? View the security audit →
Jev × WebMCP Chrome Extension A Chrome extension that uses Jev, TypeSafe's System One model, to select and populate WebMCP tool calls from user input. The side panel discovers tools exposed by the current page and displays predicted calls, confidence scores, and latency as the user types. Tool selection is derived from the page's schemas, without site-specific configuration. How schema conversion works WebMCP exposes named tools with descriptions, parameter schemas, enums, and annotations. Jev accepts state and typed questions (Choice, Score, Noul) and returns typed answers with probabilities. It answers the questions in parallel and does not generate text. The panel converts tool schemas into questions as follows: an
| Stars | 125 |
| Forks | 7 |
| Language | JavaScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 73.2025054069738/100 |
| Last Updated | 2026-09-20 |
| Created | 2026-09-19 |
| Platforms | browser, mcp, node |
| Est. Tokens | ~14k |
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jev-webmcp-extension is A small extension that demos the combination of Jev x WebMCP. It is categorized as a MCP Server with 125 GitHub stars.
jev-webmcp-extension is primarily written in JavaScript. It covers topics such as chrome, extension, extension-chrome.
You can find installation instructions and usage details in the jev-webmcp-extension GitHub repository at github.com/sdras/jev-webmcp-extension. The project has 125 stars and 7 forks, indicating an active community.
jev-webmcp-extension is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to jev-webmcp-extension on Agent Skills Hub include doma, phi, Maple. 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: