mcp server
pkgxray
Pre-install security scans for npm packages, MCP servers, and AI agents with cited verdict evidence.
Description as published by the maintainer. Source
- version 1.0.5
- active
- security
active — Most recent push to the repository was 2026-08-06. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 11 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-08-06 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 2 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.0.5 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-29 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-07-29 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub |
Where to get it
Related, by what their authors tagged them
-
Aegis — AI Agent Governance
— last commit 2026-05-05, shares ai-agent-security, mcp-security, prompt-injection
Policy-based governance for AI agent tool calls. YAML policy, approval gates, audit logging.
-
ai.marchward/mcp-server
— last commit 2026-07-01, shares ai-agent-security
Runtime authority for AI agents: credential mediation, spend cap, approval gates, audit log.
-
io.github.calllint/calllint
— last commit 2026-08-06, shares prompt-injection, static-analysis, supply-chain-security
Static preflight safety gate for MCP servers — scan configs before you run them. Never executes.
-
Bawbel Scanner
— last commit 2026-07-05, shares devsecops, mcp-security, prompt-injection
Security scanner for MCP servers and skill files. Detects AVE vulnerabilities before production.
-
Bawbel Scanner
— last commit 2026-07-05, shares devsecops, mcp-security, prompt-injection
Security scanner for MCP servers and skill files. Detects AVE vulnerabilities before production.
-
Draugr
— last commit 2026-08-06, shares devsecops, supply-chain-security
Security scanning for AI agents: SAST, SCA, secrets, IaC, DAST, ranked by real risk.
-
Bomly
— last commit 2026-08-03, shares devsecops, supply-chain-security
Give your coding agent the dependency graph it is about to change: scan, diff, explain, audit
-
DepScope
— last commit 2026-05-05, shares npm, supply-chain-security
Package intelligence MCP for AI agents — 22 tools, 19 ecosystems, AGPL SDK, free.
-
ToolTrust Scanner
— last commit 2026-08-06, shares prompt-injection, supply-chain-security
Scans MCP servers for prompt injection, data exfiltration, and privilege escalation.
-
io.github.caglarbozkurt/heimdall
— last commit 2026-07-06, shares prompt-injection, supply-chain-security
Scan an MCP server or agent config for injection, exfiltration, and risky capabilities.
These share tags the maintainers applied themselves, such as ai-agent-security, mcp-security, prompt-injection, static-analysis. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: ai-agent-security, ai-agents, devsecops, mcp, mcp-security, model-context-protocol, npm, npm-security, prompt-injection, static-analysis, supply-chain-security.
Bring your own setup
We take apart real AI setups every week and show what broke, what cost too much, and what the trace actually said. If you run agents on real work, that is where the useful conversation is.
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