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A Model Context Protocol (MCP) server for YouTube data crawling with AI summarization
We found this by crawling public sources and nobody has attested to it. That is how most of the registry gets here, and it is not a mark against the artifact — it only means no authenticated act of publication is on record. An artifact can be the vendor's own and still appear here.
Choose your runtime: the CLI writes the mcpServers config entry for that target.
nerlo install --target claude-code -- youtube-crawler-mcp
Install respects the composite badge: Clean proceeds, Caution prompts for confirmation, and Flagged is refused. Write operations require an API token.
4 of 11 scanners examined this package. The rest do not apply to it — language, ecosystem and packaging decide which analyzers can say anything, and a scanner that cannot examine an artifact reports nothing rather than passing it.
v2.0.11
2 findings · 7.8s
v0.3.74
15 findings · 1.3s
v0.1.0
0 findings · 3.7s
v0.1.0
0 findings · 3.7s
v1.4.0
None of the entry points this scanner reads were found in this artifact. What each scanner covers
0 findings · 0.2s
vv0.3.2
No Go packages were found in this artifact. What each scanner covers
0 findings · 0.1s
v0.1.0
This scanner found nothing in this artifact that it assesses. What each scanner covers
0 findings · 2.0s
No report in this scan: govulncheck, osv-scanner, trivy, trivy_image.
1 scan on record. Every scan's full results are retained immutably for 24 months.
| Completed | Composite | Change | Scanners | Status |
|---|---|---|---|---|
| Aug 21, 2026 | Scan Halted | — | agentshield ·n/a: not applicablecisco-skill-scanner: completeagent-audit-kit: completenerlo-behavioral: completenerlo-install-instruction: completecapslock ·n/a: not applicablenerlo-multi-source ·n/a: not applicable | rejected |
Findings in files this artifact installs stand as reported; a model re-read the rest and said which ones it believes are false positives. This is a second opinion published beside the evidence, not a correction to it: the per-scanner reports above are unchanged, every dismissed finding is still listed there at its original severity, and the score and the Flagged badge are computed from those raw severities alone. Nothing below moved them.
Out of 17 findings across every scanner that examined this package.
These findings are in files this artifact installs and are not placeholder values. No false-positive basis can be corroborated for such a finding, so this review never dismisses one; they were not sent to the model and stand at their scanner's severity.
3 AAK-LOGINJ-001
Files: src/fastmcp_server.py · reported by agent-audit-kit
2 AAK-MCP-003
Files: mcp_config.json · reported by agent-audit-kit
2 AAK-SECRET-007
Files: mcp_config.json · reported by agent-audit-kit
1 AAK-DNS-REBIND-002
Files: pyproject.toml · reported by agent-audit-kit
1 AAK-MCP-ATTEST-001
Files: mcp_config.json · reported by agent-audit-kit
1 AAK-MCP-HTTP-NOAUTH-SERVER-001
Files: Dockerfile · reported by agent-audit-kit
1 AAK-MCP-SDK-CVE-2026-52869-001
Files: pyproject.toml · reported by agent-audit-kit
1 AAK-OAUTH-3P-001
Files: pyproject.toml · reported by agent-audit-kit
1 AAK-SEC-MD-001
Files: SECURITY.md · reported by agent-audit-kit
1 AAK-SSRF-002
Files: src/fastmcp_server.py · reported by agent-audit-kit
1 AAK-SUPPLY-004
Files: pyproject.toml · reported by agent-audit-kit
1 MANIFEST_MISSING_LICENSE
Files: /repo/SKILL.md · reported by cisco-skill-scanner
1 SOCIAL_ENG_VAGUE_DESCRIPTION
Files: /repo/SKILL.md · reported by cisco-skill-scanner
Artifact contains multiple high-severity vulnerabilities.
The artifact exposes an unauthenticated HTTP server via its Dockerfile and is susceptible to Server-Side Request Forgery in `src/fastmcp_server.py`, which could lead to network egress. Configuration files (`mcp_config.json`) contain sensitive settings, and a DNS rebind vulnerability is present in `pyproject.toml`. Additionally, a critical vulnerability (CVE-2026-52869) is identified in a dependency listed in `pyproject.toml`.
Concern level assessed by the review: High. This is the review's scale, not the registry badge.
Reviewed by gemini-2.5-flash. The model sees the findings, not your code, and cannot change a score.