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An MCP server that lets any AI client generate anime images via a local Stable Diffusion XL (Animagine XL) backend.
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 -- anime-sd-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
5 findings · 6.4s
v0.3.74
6 findings · 1.3s
v0.1.0
2 findings · 2.8s
v0.1.0
0 findings · 2.8s
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 · 1.7s
v0.71.0
No dependency manifest or lockfile was found in this artifact. What each scanner covers
0 findings · 0.2s
v2.3.8
No dependency manifest or lockfile was found in this artifact. What each scanner covers
0 findings · 0.2s
v0.71.0
No container image was published for this artifact. What each scanner covers
0 findings · 0.0s
vv1.6.0
No Go modules were found in this artifact. What each scanner covers
0 findings · 0.1s
1 scan on record. Every scan's full results are retained immutably for 24 months.
| Completed | Composite | Change | Scanners | Status |
|---|---|---|---|---|
| Aug 20, 2026 | Flagged74 | — | 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 applicabletrivy ·n/a: not applicableosv-scanner ·n/a: not applicabletrivy_image ·n/a: not applicablegovulncheck ·n/a: not applicable | completed |
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 13 findings across every scanner that examined this package.
Not reviewed is not the same as clean. Those 4 findings stand exactly as their scanners reported them, at full severity, as they would have without this review.
The model could have called any of these a false positive and did not.
2 DATA_EXFIL_NETWORK_REQUESTS
Files: /repo/src/anime_sd_mcp/server.py · reported by cisco-skill-scanner
2 opt.nerlo-rules.nerlo-py-secret-to-network-egress
Files: /repo/src/anime_sd_mcp/server.py · reported by nerlo-behavioral
1 AAK-DNS-REBIND-002
Files: pyproject.toml · 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-SSRF-002
Files: src/anime_sd_mcp/server.py · reported by agent-audit-kit
1 AAK-SUPPLY-004
Files: pyproject.toml · reported by agent-audit-kit
4 The model called these false positives and our own check did not agree, so the dismissal was refused.
Rules: TOOL_ABUSE_UNDECLARED_NETWORK, AAK-SEC-MD-001, SOCIAL_ENG_VAGUE_DESCRIPTION and 1 more · Files: /repo/repo/README.md, SECURITY.md, /repo/SKILL.md · reported by cisco-skill-scanner, agent-audit-kit
High-risk network egress, SSRF, and dependency vulnerabilities.
The artifact presents high-risk network capabilities, including potential Server-Side Request Forgery (SSRF) and the egress of secrets over the network, both identified in `src/anime_sd_mcp/server.py`. High-severity findings also indicate a DNS rebinding vulnerability and a specific CVE (CVE-2026-52869) related to a dependency, noted in `pyproject.toml`. Additionally, medium-severity findings highlight undeclared network activity, third-party OAuth integration, and supply chain risks.
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.