ClassiFinder MCP Server

An MCP server that gives AI agents the ability to scan text for leaked secrets and redact them before they reach an LLM.

Installation

pip install classifinder-mcp

Related MCP server: trustboost-pii-sanitizer

Setup

Get a free API key at classifinder.ai, then add to your agent config:

Claude Code

{
  "mcpServers": {
    "classifinder": {
      "command": "classifinder-mcp",
      "env": {
        "CLASSIFINDER_API_KEY": "ss_live_your_key_here"
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "classifinder": {
      "command": "classifinder-mcp",
      "env": {
        "CLASSIFINDER_API_KEY": "ss_live_your_key_here"
      }
    }
  }
}

Tools

classifinder_scan

Scan text for leaked secrets and credentials. Returns findings with type, severity, confidence, and remediation guidance.

Agent: "Check this config for secrets"
→ classifinder_scan(text="AWS_ACCESS_KEY_ID=AKIAJGKJHSKLDJFH3284")
→ Found 1 secret: aws_access_key (critical, confidence 0.95)

classifinder_redact

Replace all detected secrets with safe placeholders. Returns clean text safe to forward to any LLM.

Agent: "Clean this before sending to the model"
→ classifinder_redact(text="key=sk_live_EXAMPLE_KEY_HERE")
→ "key=[STRIPE_LIVE_SECRET_KEY_REDACTED]"

What It Detects

297 detection patterns:

• 283 secret types across 10 categories: cloud/infra keys (AWS, GCP, Azure, Vercel including the 2024+ prefixed taxonomy vcp_/vci_/vca_/vcr_/vck_, Fly.io, Doppler, HashiCorp Vault, Cloudflare, Dropbox, JFrog/Artifactory and more); payment (Stripe, PayPal, Shopify with 4 token types, credit cards Luhn-validated, Square); VCS (GitHub, GitLab with 10 token types covering deploy/feed/runner/SCIM/k8s-agent/OAuth/feature-flag, Bitbucket); comms/SaaS (Slack including config/session/legacy variants, Twilio, SendGrid, Mailgun, Datadog, Sentry, PagerDuty, Notion, Linear and more); database connection strings (PostgreSQL/MySQL/MongoDB/Redis/Supabase); generic SSH/PEM private keys and JWTs; AI/LLM provider keys (OpenAI, Anthropic user + admin, Cohere, xAI, Mistral, DeepSeek, HuggingFace user + organization, Replicate, Groq, ElevenLabs, AssemblyAI, Deepgram, LangFuse, AWS Bedrock long + short-lived, Vercel AI Gateway, Weights & Biases); DevOps/CI-CD/observability (Databricks, Dynatrace, LaunchDarkly, Harness, Octopus Deploy, Fastly, Gitea, TravisCI, Prefect, Infracost, Sumo Logic, Snyk, Sonar, Sourcegraph); data/analytics (ClickHouse, PlanetScale, PostHog, Postman, Algolia, Contentful); and enterprise identity (Atlassian, 1Password, HubSpot, Mapbox, MaxMind, Zendesk).

• 14 prompt-injection markers for LLM input scanning — 4 phase-1 high-precision (chat-template role-hijack tokens like <|im_start|> and [INST], tool-call tag injection, known jailbreak personas like DAN/AIM, Unicode bidirectional override / Trojan Source) + 6 phase-2 medium-precision (zero-width Unicode smuggling, fake "Assistant:" turns, system-prompt extraction, instruction override like "ignore previous instructions", persona override (context-gated), encoded-payload markers) + 4 phase-3 SAFE-MCP-derived markers cross-referenced to the SAFE-MCP technique catalog. Catches 20.6% of in-the-wild jailbreaks (validated against the verazuo/jailbreak_llms corpus). Severity caps at high — these are attack markers, not credentials.

One scan returns both secret findings and injection markers — no second vendor, no separate pipeline.

Hardening — Sandbox Profiles

The MCP server is intentionally minimal: ~180 lines, two read-only tools, a single egress destination (api.classifinder.ai:443), and the API key as the only secret in scope. That makes it cheap to run under a sandbox. Three documented profiles:

Docker

docker run --rm -i \
  --read-only \
  --tmpfs /tmp \
  -v ~/.classifinder:/root/.classifinder \
  -e CLASSIFINDER_API_KEY \
  python:3.12-slim sh -c "pip install -q classifinder-mcp && classifinder-mcp"

• --read-only — container filesystem is read-only

• --tmpfs /tmp — writable scratch space for pip / Python

• -v ~/.classifinder:/root/.classifinder — only persistent mount, used for the audit log

• -e CLASSIFINDER_API_KEY — key passed via env, never written to disk

• -i — keeps stdin attached (MCP transport is stdio)

For a faster invocation in production, build a thin image with classifinder-mcp pre-installed.

Firejail (Linux)

firejail \
  --noroot \
  --caps.drop=all \
  --seccomp \
  --private-tmp \
  --whitelist=~/.classifinder \
  --read-only=~ \
  --read-write=~/.classifinder \
  classifinder-mcp

• Drops all capabilities + applies a default seccomp filter

• Filesystem: home is read-only, only ~/.classifinder/ writable

• Process runs without root privilege escalation

• Network egress remains open (required for api.classifinder.ai) — pair with host-level egress filtering (ufw, iptables, or nftables) if you want network restriction

Bubblewrap (Linux)

bwrap \
  --ro-bind / / \
  --bind ~/.classifinder ~/.classifinder \
  --proc /proc --dev /dev --tmpfs /tmp \
  --unshare-pid --unshare-uts --new-session --die-with-parent \
  --setenv CLASSIFINDER_API_KEY "$CLASSIFINDER_API_KEY" \
  classifinder-mcp

• Read-only bind mount of /; writable bind only for ~/.classifinder/

• Fresh PID + UTS namespaces; new session

• --die-with-parent ensures the sandbox tears down if the host process exits

• API key passed via setenv, no file mount needed

Verification

These profiles are documented starting points. None are exercised in this repo's CI — they're correctness-by-construction (read-only bind mounts, dropped caps, single-purpose tmpfs) rather than test-validated. If you run a sandbox in production and want me to roll a verified profile into a future release, open an issue with the exact invocation you're using.

Audit Log

The MCP server appends one JSONL line per tool call to a local audit file. Metadata only — the audit log never contains your input text or any detected secret values.

Default path: ~/.classifinder/mcp-audit.log

Fields per line:

{
  "timestamp": "2026-05-22T15:30:42.123456Z",
  "tool": "classifinder_scan",
  "input_byte_count": 142,
  "finding_count": 1,
  "latency_ms": 87.4
}

Configuration (env vars):

The audit log is observability for your own use — useful for compliance (proving the MCP server ran), debugging (correlating latency spikes), and forensic review (which tool ran when). Write failures are silent; the tool call always succeeds even if the audit cannot be written.

Verifying a Release

Every published release is signed twice:

1. PyPI attestations (PEP 740) — minted by PyPI from this repo's OIDC identity during publish. Verified automatically by pip when installing from PyPI; you don't need to do anything.

2. Sigstore bundles — published as GitHub Release assets (*.sigstore.json next to the sdist + wheel). Verify with sigstore-python:

pip install sigstore
gh release download v0.1.4 --repo ClassiFinder/classifinder-mcp \
  --pattern '*.whl' --pattern '*.sigstore.json'

sigstore verify identity \
  --bundle classifinder_mcp-0.1.4-py3-none-any.whl.sigstore.json \
  --cert-identity 'https://github.com/ClassiFinder/classifinder-mcp/.github/workflows/release.yml@refs/tags/v0.1.4' \
  --cert-oidc-issuer 'https://token.actions.githubusercontent.com' \
  classifinder_mcp-0.1.4-py3-none-any.whl

The signing identity binds the artifact to this repo's release.yml workflow at a specific tag — an attacker can't forge a valid bundle without compromising GitHub's OIDC token issuance.

See Also

For CLI scanning instead of MCP, see cfsniff — a command-line tool that scans files, shell history, and configs for secrets (pipx install cfsniff).

Disclaimer

ClassiFinder is a detection aid, not a guarantee. No scanner catches 100% of secrets in 100% of formats. See our Terms of Service for full details.

License

MIT