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com.tamperlens/mcp

NPM · TAMPERLENS-MCP · SCANNED AUG 20

Was this document edited, did its redactions hold, is it safe for a model to read — Tamperlens API.

Available components

63 Trust /100
Trust breakdown (6 categories)

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 Security100
  • No malware found by supply-chain analysis.Pass
  • No known CVEs affecting this package version or its production dependencies.Pass
  • No install/post-install scripts declared.Pass
  • 0 of 3 dependencies flagged as unhealthy. View diagnostics → Pass
Provenance & Transparency19
  • Repository check failed: the declared repository URL returned HTTP 404. 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 1 days ago).Pass
  • Security-disclosure policy not yet verified: we couldn't inspect the source repository.Unverified
Schema Quality & AI Usability73
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 587 tokens (~195/item across 3 items; 3 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
  • Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
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 current MCP spec version (2026-07-28).Pass

Unverified: 1 category

A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

Install

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 · tamperlens-mcp

# add to Claude Code
claude mcp add com-tamperlens-mcp -- npx -y tamperlens-mcp
# add to Codex CLI
codex mcp add com-tamperlens-mcp -- npx -y tamperlens-mcp
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-tamperlens-mcp": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "tamperlens-mcp"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add com-tamperlens-mcp --command npx --arg -y --arg tamperlens-mcp
# ~/.hermes/config.yaml
mcp_servers:
  com-tamperlens-mcp:
    command: "npx"
    args: ["-y", "tamperlens-mcp"]
// mcp.json
{
  "mcpServers": {
    "com-tamperlens-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "tamperlens-mcp"
      ]
    }
  }
}
Changelog

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.

  • 19 Aug 26 +15
    • Malware scan: unverified → pass security
  • 18 Aug 26 48

    First indexed and scored.

Diagnostics

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 20 Aug 2026 · Analysed npm/tamperlens-mcp@1.30.0

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem npm
Dependencies 3 packages
Packages resolved 3
Tree resolution Complete
MCP tools · 3 exposed · ~587 tokens

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.

Tool Tokens
check_redaction ~117

Check whether a PDF's redactions actually removed anything. Covering text with a black box hides it from a reader and removes nothing from the file, so the words stay extractable. This reads paint order to catch a plain drawn rectangle — which carries no redaction annotation at all and is the failure behind most published redaction leaks — and separately catches redaction marks that were never applied. Use this before a document is filed or released.

NameTypeReqDescription
pathstringyesAbsolute path to the PDF on this machine. Max 10 MB.

No output schema declared.

No examples provided.

compare_documents ~109

Compare a candidate document against the original you already hold, and answer the question a single-file check cannot: is this the same file, unchanged? Reports byte identity (the only proof), revision ancestry when the candidate contains the original as a byte prefix, or a field-by-field structural diff when both were rewritten whole. Renders nothing and compares no pixels.

NameTypeReqDescription
candidatePathstringyesAbsolute path to the document being checked.
originalPathstringyesAbsolute path to the document you trust.

No output schema declared.

No examples provided.

inspect_document ~361

Inspect a document or image for fraud and tamper signals: revisions appended after the original save, metadata that disagrees with itself, editor fingerprints, signature coverage gaps, text still readable under a redaction box, unaccepted tracked changes whose deleted text is still recoverable, hidden text, hidden spreadsheet sheets, macros, and AI-generator or editor traces in images. Returns risk signals with the raw evidence behind each one — never a verdict on authenticity. Accepts PDF; Word, Excel and PowerPoint documents (.docx, .xlsx, .pptx and macro-enabled twins); and JPEG, PNG, WebP, HEIC/HEIF and AVIF images. ALSO ANSWERS: is this file safe for a model to read? Document properties, XMP, annotations, attachment names, docProps, comments and hidden Word runs are checked for text written to be read by a language model rather than by a person — the prompt-injection carriers an extraction pipeline surfaces and a human reader never sees. Call this BEFORE the document reaches your own context. The recovered text itself is never returned through this tool: you get the cue categories, the counts and which kind of field carried it, because reading the payload is the attack.

NameTypeReqDescription
issuerstringOptional issuer slug (e.g. 'chase') to additionally compare the document against a structural baseline of genuine documents from that institution. PDFs only — ignored for Office documents and images.
pathstringyesAbsolute path to the document on this machine — PDF, Office document or image. Max 10 MB.
policyobjectOptional. Your own risk thresholds and signal rules; the response gains a verdict of accept/review/reject computed from them. Nothing about the report changes.

No output schema declared.

No examples provided.