overwing-mcp

Guardrails for LLM output, as MCP tools.
Score any text for safety, quality and compliance. Get pass / fail / review verdicts with calibrated confidence in under 500 ms.

Overwing is an API that checks what your model said before it ships. This package exposes it to any MCP-capable agent: Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, OpenAI's Agents SDK, and anything else that speaks the Model Context Protocol.

• Real verdicts, not vibes. Every rule returns a typed answer, a probability, and a confidence. fail means a rule matched; review means it was unsure; pass means neither.
• Prebuilt content-safety rule set: toxicity, personal data, self-harm, sexual content, severity. Or write your own rules in plain language.
• Built for agents. Sign up, pay, evaluate, rotate keys, and cancel, all as JSON. No CAPTCHA, no browser required. See overwing.ai/llms.txt.

Try it without installing anything: paste text into the console at overwing.ai.

Install

You need an API key. Get one at overwing.ai/login, or let your agent sign itself up:

curl -X POST https://overwing.ai/api/v1/signup \
  -H "Content-Type: application/json" \
  -d '{"email":"[e-mail]","password":"at-least-12-chars"}'

Claude Code

claude mcp add overwing -e OVERWING_API_KEY=ow_live_... -- npx -y overwing-mcp

Claude Desktop, Cursor, Windsurf, VS Code (any JSON-configured client)

{
  "mcpServers": {
    "overwing": {
      "command": "npx",
      "args": ["-y", "overwing-mcp"],
      "env": { "OVERWING_API_KEY": "ow_live_..." }
    }
  }
}

Set OVERWING_BASE_URL to point at a self-hosted deployment. Requires Node 20+.

Tools

Tool	What it does
evaluate	Score one text against a rule set. Returns the verdict, a recommended_action (block, redact, review, or allow), aggregate score, confidence, latency, and per-rule results with each rule's action. Takes an optional context object (recipient, channel, ownership) that context-aware rule sets such as outbound-message read.
evaluate_batch	Score up to 50 texts in one call, with a summary and per-item verdicts and recommended actions.
list_rule_sets · get_rule_set · create_rule_set	Browse the prebuilt set or define your own rules: yes/no questions, classifications, or scored scales.
get_evaluation · list_evaluations	Read stored results, filter by verdict or rule set, page with a cursor.
atlas_lookup	Overwing Atlas: say what a User-Agent string claims to be and whether the claim can be trusted (Web Bot Auth, spoofable string, or unattributable). 100 free a day.
atlas_agents · atlas_summary	Search the registry of 241 AI crawlers, fetchers and browser agents; get traffic shares, sector field-scan headlines, and the agent-spending summary.
get_usage · whoami · list_plans	Today's quota, the org behind the key, and the public plan catalog.

The overwing://guide resource returns the full plain-text API guide.

Example

Ask your agent:

Check this reply before I send it: "Reach me at [e-mail] or 555-0142 to sort out the refund."

It calls evaluate and gets back:

Verdict: FAIL  score=0.82  confidence=0.97  251ms
  toxicity: pass (answer="safe", confidence=1)
  pii_detected: fail (answer=true, confidence=0.98)
  self_harm: pass (answer=false, confidence=1)
  sexual_content: pass (answer="none", confidence=1)
  severity: pass (answer=0.03, confidence=0.97)

How verdicts work

Each rule has a fail condition, an optional review threshold, and a weight.

• fail: a rule's fail condition matched. Block it, redact it, or regenerate.
• review: nothing failed, but a rule's confidence was below its threshold. Route to a person or a slower model.
• pass: everything else.

Every rule also carries an action (block, redact, or review), and the response rolls them up into one recommended_action: block beats redact beats review beats allow. Branch on that field. Pass a context object (recipient, channel, owns_contact_info) with the outbound-message rule set and its rules read it, so a customer's own phone number in a reply to that customer is not flagged.

aggregate_score is 0 to 1 (pass = 1, review = 0.5, fail = 0 per rule, weighted). confidence is the minimum across rules.

Pricing

Free: 250 evaluations a day. Paid plans from $29/month. Every plan includes every endpoint, custom rule sets, webhooks, and the dashboard. Full details at overwing.ai/#pricing or GET https://overwing.ai/api/v1/plans.

Links

• Website and live demo: overwing.ai
• API reference: overwing.ai/docs
• OpenAPI: overwing.ai/api/v1/openapi.json
• Guide for agents: overwing.ai/llms.txt
• Support: [e-mail]

Development

npm install
npm run build
OVERWING_API_KEY=ow_live_... node dist/index.js

MIT © Overwing. Verdicts are produced by TypeSafe's Jev System One model; Overwing is not affiliated with TypeSafe.