AI Scanner
NPM · AI-SCANNER-MCP · SCANNED AUG 3
Scan codebases for LLM/AI SDK usage, exposed API tokens, and hardcoded secrets.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score →
Supply Chain Security87
- No malware found by supply-chain analysis.Pass
- Only part of the dependency tree could be resolved (96 of 100), so this covers what we could see, not the whole tree.Partial
- No install/post-install scripts declared.Pass
- Only part of the dependency tree could be resolved (96 of 100), so this covers what we could see, not the whole tree. View diagnostics → Partial
Provenance & Transparency19
- Repository check failed: the declared repository URL redirects; it must resolve directly. See how to fix → View diagnostics → Fail
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 134 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability77
- AI-judged instruction clarity (excellent).Pass
- Tool/resource definitions use about 343 tokens (~114/item across 3 items; 3 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
- Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.
npm · ai-scanner-mcp
claude mcp add aakashbhardwaj27-ai-scanner -- npx -y ai-scanner-mcp
codex mcp add aakashbhardwaj27-ai-scanner -- npx -y ai-scanner-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"aakashbhardwaj27-ai-scanner": {
"type": "local",
"command": [
"npx",
"-y",
"ai-scanner-mcp"
],
"enabled": true
}
}
} openclaw mcp add aakashbhardwaj27-ai-scanner --command npx --arg -y --arg ai-scanner-mcp
mcp_servers:
aakashbhardwaj27-ai-scanner:
command: "npx"
args: ["-y", "ai-scanner-mcp"] {
"mcpServers": {
"aakashbhardwaj27-ai-scanner": {
"command": "npx",
"args": [
"-y",
"ai-scanner-mcp"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 2 Aug 26 +40
- Provenance: fail → unverified ▼ security
- Install scripts: pass → unverified ▼ security
- Known CVEs: unverified → partial ▲ security
- Malware scan: unverified → pass ▲ security
- License: pass → unverified ▼ functional
- Tool coverage: 100 → unverified ▼ functional
- Maintenance: pass → unverified ▼ functional
- Stability: unverified → 0.23 ▲ functional
- MCP protocol: unverified → pass ▲ functional
- Dependency health: unverified → partial ▲ functional
- Schema quality: unverified → excellent ▲ functional
- Licence: MIT functional
- 1 Aug 26 +8
- Provenance: unverified → fail ▼ security
- Install scripts: unverified → pass ▲ security
- Maintenance: unverified → pass ▲ functional
- License: unverified → pass ▲ functional
- Licence: MIT functional
- 31 Jul 26 −24
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 28 Jul 26 +22
- Tool coverage: unverified → 100 ▲ functional
- First check of Schema quality: unverified functional
- First check of Schema quality: fail functional
- First check of Schema quality: pass functional
- First check of Tool coverage: 100 functional
- 27 Jul 26 18
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 3 Aug 2026 · Analysed npm/[email protected]
Provenance none
Ecosystem: npm · Outcome: none
Dependencies 96 packages
96 packages in the resolved dependency tree · 95 deprecated · 29 stale.
The dependency tree was only partially resolved, so these counts may be incomplete.
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.
ai_inventory ~70
Get an inventory of all AI/LLM technologies used in a codebase — which SDKs are imported, which frameworks are integrated, which models are referenced, and which provider APIs are called. No secret detection, just awareness.
| Name | Type | Req | Description |
|---|---|---|---|
| directory | string | yes | Absolute or relative path to the directory to scan |
No output schema declared.
No examples provided.
check_secrets ~107
Security check — scan a directory for exposed API tokens and hardcoded secrets only. Returns pass/fail with a list of any exposed credentials found. Use this before committing code or in CI pipelines.
| Name | Type | Req | Description |
|---|---|---|---|
| ai_only | boolean | — | If true, only check for AI-specific tokens (skip Stripe, GitHub, etc.) |
| directory | string | yes | Absolute or relative path to the directory to scan |
| scan_env | boolean | — | If true, include .env files in the scan |
No output schema declared.
No examples provided.
scan_directory ~166
Scan a directory for LLM SDK usage, AI frameworks, exposed API tokens, and hardcoded secrets. Returns all findings grouped by type (token, secret, sdk, framework, endpoint, model) with file locations and severity levels.
| Name | Type | Req | Description |
|---|---|---|---|
| ai_only | boolean | — | If true, only scan for AI-specific patterns (skip generic secrets like Stripe, GitHub tokens, etc.) |
| directory | string | yes | Absolute or relative path to the directory to scan |
| include_endpoints | boolean | — | If true, detect LLM API endpoint URLs |
| include_models | boolean | — | If true, detect model name references (gpt-4, claude, etc.) |
| scan_env | boolean | — | If true, include .env files in the scan (skipped by default) |
No output schema declared.
No examples provided.