Compuute MCP Security Scanner

Clones the repo (shallow, <60s, <200 MB), runs compuute-scan v0.6.2 in
static analysis mode (no code execution from the target), and returns a
structured report with severity counts, a 0-100 score, and the 10 most
severe findings.

WHEN TO USE:
  - Before connecting to an unknown MCP server discovered via Anthropic
    Registry, Smithery, mcp.so, or a Discord recommendation.
  - Before installing a third-party MCP-server package into a production
    pipeline.
  - As part of an agent's pre-commit / pre-deploy due-diligence step
    when adding new dependencies.
  - As one input to a multi-source trust evaluation (combine with
    publisher reputation, package install count, last-update recency).

WHEN NOT TO USE:
  - For private repos. Use the on-prem CLI instead:
      `npx compuute-scan ./path-to-private-repo`
  - For deep exploitability assessment of a specific code path. This is
    pattern matching, not dataflow analysis. Book a manual L2-L4 audit
    at https://compuute.se/audit for that depth.
  - For non-GitHub hosts (GitLab, Bitbucket, self-hosted). v1 supports
    github.com only.
  - For repos > 200 MB or clone time > 60s. The endpoint returns a 413
    or 504 in those cases — fall back to local CLI.

EXPECTED RESPONSE TIME:
  - Median: ~1-2 seconds for small repos (<100 files).
  - p99: ~10 seconds for medium repos.
  - Hard timeout at clone=60s, scan=120s combined.

EXPECTED COST:
  - Free tier in MVP. Future Pro tier may charge per-scan or per-month.

DATA FRESHNESS:
  - Scanner version is reported in response.scanner.version.
  - L1 rule set freshness reflects compuute-scan releases — see
    github.com/Compuute/compuute-scan/CHANGELOG.md for the latest CVE
    and threat-intel response timeline.

EXAMPLES:

  Example 1 — scan an MCP server you're evaluating:
    github_url = "https://github.com/modelcontextprotocol/servers"
    → score: 0, summary: {critical: 1, high: 94, medium: 22}
    → top_findings include SSRF, eval, etc.
    → recommendation: "AVOID — 1 critical and 94 high finding(s)..."

  Example 2 — scan a clean reference implementation:
    github_url = "https://github.com/microsoft/azure-devops-mcp"
    → score: 90+, summary: {critical: 0, high: 1}
    → recommendation: "REVIEW — 1 high finding(s)..."

  Example 3 — scan your own dev MCP-server before publishing:
    github_url = "https://github.com/yourorg/your-mcp"
    → audit your own surface before others install it

OUTPUT FIELDS (stable schema):
  - repo_url (str): canonical URL of the scanned repo.
  - score (int): 0-100, higher safer. Coarse summary, not a precision claim.
  - summary (object): {critical, high, medium, low, info, files_scanned}.
  - recommendation (str): action guidance derived from severity counts.
  - findings_count (int): total raw findings (may include false positives).
  - top_findings (list): up to 10 most severe, each with {id, title,
    severity, file, line, owasp, cwe}.
  - l0_discovery (object): MCP transport, tool count, dependency pinning.
  - performance (object): clone_seconds, scan_seconds, repo_size_bytes.
  - scanner (object): {name, version, layers_covered}.
  - _disclaimer (str): MANDATORY triage disclaimer. Read it.

Args:
  github_url: Public GitHub HTTPS URL (e.g. https://github.com/org/repo).
              Must be public and < 200 MB. v1 is github.com only.

Returns:
  Structured scan result. On error, returns {"error": code, "message": ...}
  with HTTP-style code (invalid_url, clone_failed, scan_timeout, etc.).