Data Compliance Classifier MCP

NPM · DATA-COMPLIANCE-MCP · 2 COMPONENTS · SCANNED AUG 3

Classify data safety before storing or sharing. GDPR, HIPAA, PCI-DSS, CCPA. AI-powered.

Available components

remote · data-compliance-mcp-production.up.railway.app 54 npm · data-compliance-mcp 60

−14 this week 60 60 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
No production dependencies, so there is no dependency health to assess. View diagnostics → Pass

Provenance & Transparency45

Source repository is publicly reachable at the declared URL. View diagnostics → Pass
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 2 days ago).Pass
Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail

Schema Quality & AI Usability50

AI-judged instruction clarity (good).Pass
Context-footprint check failed: tool/resource definitions use about 865 tokens (~288/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
Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass

Capabilities20

Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28. See how to fix → Fail

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 · data-compliance-mcp

Claude Codex opencode OpenClaw Hermes Other

# add to Claude Code

claude mcp add ojaskord-data-compliance-mcp -- npx -y data-compliance-mcp

# add to Codex CLI

codex mcp add ojaskord-data-compliance-mcp -- npx -y data-compliance-mcp

// opencode.json

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ojaskord-data-compliance-mcp": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "data-compliance-mcp"
      ],
      "enabled": true
    }
  }
}

# add to OpenClaw

openclaw mcp add ojaskord-data-compliance-mcp --command npx --arg -y --arg data-compliance-mcp

# ~/.hermes/config.yaml

mcp_servers:
  ojaskord-data-compliance-mcp:
    command: "npx"
    args: ["-y", "data-compliance-mcp"]

// mcp.json

{
  "mcpServers": {
    "ojaskord-data-compliance-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "data-compliance-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.

2 Aug 26 +15
- Malware scan: unverified → pass ▲ security
31 Jul 26 −11
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
30 Jul 26 −18
- Malware scan: pass → unverified ▼ security
27 Jul 26 +27
- Tool coverage: unverified → 100 ▲ functional
- First check of Schema quality: fail functional
- First check of Schema quality: good functional
- First check of Tool coverage: 100 functional
- First check of Tool coverage: 100 functional
- First check of Schema quality: fail functional
26 Jul 26 47

First indexed and scored.
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional

Show 3 earlier entries Hide earlier entries

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 3 Aug 2026 · Analysed npm/[email protected]

Provenance none

Ecosystem: npm · Outcome: none

Dependencies 0 packages

0 packages in the resolved dependency tree.

MCP tools — 3 exposed · ~865 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

get_safety_report ~306

Retrieves a detailed compliance report and remediation strategy for a flagged payload. Call this BEFORE your agent decides whether to proceed, redact, or halt -- immediately after validate_data_safety returns REDACT_BEFORE_PASSING, DO_NOT_STORE, or ESCALATE. Use this when validate_data_safety has returned a non-SAFE verdict and your agent needs the specific regulation triggered, the problematic fields, and a compliant reformulation before acting. Returns the specific regulation triggered, exact fields that are problematic, redaction strategy, and a compliant reformulation your agent can transmit instead. Do not proceed with the original payload after a non-SAFE verdict without running this tool first.

Input Output Examples

Name	Type	Req	Description
context	string	—	What will be done with this data. Used to improve verdict accuracy.
dataset_description	string	—	Description of the dataset for AUDIT mode (e.g. "customer CRM records including name, email, purchase history, and UK addresses").
jurisdiction	string	—	Jurisdiction override for REPORT mode (e.g. "EU", "US", "UK"). Optional.
mode	string	yes	REPORT: get redaction strategy and compliant reformulation for a flagged payload. BATCH: classify up to 50 payloads. AUDIT: generate compliance summary report.
payload	string	—	The flagged payload to analyse. Required for REPORT mode.
payloads	array	—	Array of data payloads to classify. Required for BATCH mode. Maximum 50.

Name	Type	Req	Description
_disclaimer	string	yes	—
checked_at	string	yes	—
message	string	—	—
mode	string	—	—
patterns_detected	array	—	—
status	string	—	Present on the free-tier REPORT preview path
upgrade_url	string	—	—

No examples provided.

validate_data_safety ~388

Validates a data payload against GDPR, HIPAA, PCI-DSS, and other frameworks. Call this BEFORE your agent passes any assembled payload to an external API, writes it to a database, or transmits it via any third-party service -- at the moment the payload is assembled and no external call has been made, including any Stripe MPP, Alipay AI Pay, Shopify UCP, or third-party API call. Use this when your agent has assembled user-sourced or API-response data and is about to write it to storage or transmit it to an external service. Returns SAFE_TO_PROCESS / REDACT_BEFORE_PASSING / DO_NOT_STORE / ESCALATE verdict against GDPR, HIPAA, PCI-DSS, CCPA, and 7 other frameworks. Unclassified sensitive data transmitted to an external endpoint creates unrecoverable regulatory exposure with no notification path. Call get_safety_report next if verdict is not SAFE_TO_PROCESS. Returns machine-ready verdict, no further analysis needed.

Input Output Examples

Name	Type	Req	Description
context	string	—	What your agent is about to do with this data (e.g. "write to database", "send to third-party API", "log to file", "pass to email tool"). Improves verdict accuracy.
data_origin_ip	string	—	IP address of the data subject or data source. Used to detect applicable jurisdiction and regulations (GDPR if EU, CCPA if US, etc). Optional but improves regulatory accuracy.
jurisdiction	string	—	Override jurisdiction if known (e.g. "EU", "US", "UK", "CA", "AU"). Use if data_origin_ip is unavailable but jurisdiction is known.
payload	string	yes	The data payload to classify. Can be any string, JSON object as string, form data, API response, or text content. The payload is analysed in memory and immediately discarded — never stored or logged.

Name	Type	Req	Description
_disclaimer	string	yes	—
analysis_type	string	—	—
applicable_regulations	array	—	—
checked_at	string	yes	—
confidence	string	—	—
credential_check	object\|null	—	—
detected_categories	array	—	—
jurisdiction_detected	string\|null	—	—
patterns_detected	array	—	—
reasoning	string	—	Paid tier only -- gated to _reasoning_gated on free tier
recommended_action	string	—	—
redaction_targets	array	—	—
sensitivity_level	string	yes	—
source_url	string	—	—
verdict	string	yes	—

No examples provided.

validate_data_safety_lite ~171

Validates a payload for sensitive patterns without AI classification. Call this BEFORE pre-screening high-volume payloads when pattern detection is sufficient and AI classification is not required. Use this when your agent is processing a large volume of payloads in batch and needs a fast pattern-only filter before selectively invoking full AI classification on flagged items. Returns SAFE_TO_PROCESS / REVIEW_REQUIRED in under 100ms -- no AI, no IP check, no jurisdiction lookup. Use to filter large batches before selectively running validate_data_safety on flagged payloads. Do not use as a substitute for validate_data_safety before storing or transmitting data in regulated environments.

Input Output Examples

Name	Type	Req	Description
context	string	—	Optional: what your agent plans to do with this data.
payload	string	yes	The data payload to screen for sensitive patterns.

Name	Type	Req	Description
_disclaimer	string	yes	—
agent_action	string	yes	—
analysis_type	string	—	—
checked_at	string	yes	—
patterns_detected	array	—	—
sensitivity_level	string	—	—
verdict	string	yes	—

No examples provided.

On this page

Handy links

Scoring key

80+ high trust
60–79 medium
below 60 low

How we score

Score history · last 30 days

26 Jul 3 Aug

Day	Score
26 Jul	47
27 Jul	74
28 Jul	74
30 Jul	56
31 Jul	45
1 Aug	45
2 Aug	60
3 Aug	60