Refd MCP Server

refd

Open-source AI search monitoring — track how AI answers talk about any brand: visibility, mentions, citations, and rank across ChatGPT, Perplexity, Gemini, Google AI Mode, and Google AI Overviews. Use the hosted app at refd.ai or self-host the whole stack.

One Cloudflare Worker runs everything: Hono API, daily cron, queue consumer, and the React dashboard (Workers Static Assets). Data via BrightData (dataset scrapers + SERP API), stored in D1 (Drizzle) with gzipped raw payloads in R2.

refd also exposes the same workspace intelligence to AI agents through a read-only, OAuth-protected remote MCP connector. See the MCP connector guide for Claude, Claude Code, ChatGPT, and self-hosting setup.

How it works

Accounts hold workspaces; each workspace tracks one brand — its competitors, its prompt set, its runs. A daily cron creates an idempotent run for every workspace eligible for scheduled monitoring, then fans out queue messages: one batch-snapshot trigger per dataset surface × sample (trigger → notify → fetch, with a backstop poll), plus one sync SERP call per prompt × sample for AI Overviews. Every answer is scored for every tracked entity (mentioned / cited / first-mention position), and the raw payload is archived gzipped in R2. A missing AI Overview is recorded as a valid "no AIO shown", not a failure. Retries honor Retry-After, back off with jitter, and are idempotent at every layer — a redelivered message never re-spends provider quota.

Develop

bun install
bun run dev    # applies local migrations, starts vite + Caddy → https://refdlocal.io

Register on the login screen (business email + password ≥ 8 chars) — your first workspace is created automatically and drops you into a resumable setup wizard: name your brand, let it draft your description from your site, pick competitors and prompts, choose engines, then watch the first report fill in live. Every AI step falls back to typing it yourself. Standard accounts can create up to five workspaces, keep up to 25 active prompts in each, and enable up to three AI surfaces. Emails in ADMIN_EMAILS have no workspace or active-prompt cap and can enable all available surfaces.

bun run dev also starts Caddy (Caddyfile) fronting vite at https://refdlocal.io (needs 127.0.0.1 refdlocal.io in /etc/hosts and a one-time caddy trust); Caddy stops when dev exits. Plain http://localhost:5173 works too.

Local secrets go in .dev.vars (gitignored): JWT_SECRET, BRIGHTDATA_API_TOKEN, BRIGHTDATA_WEBHOOK_SECRET (optional locally; requires a publicly reachable PUBLIC_BASE_URL), ADMIN_EMAILS (comma-separated administrator and operator allowlist), and EXA_API_KEY (onboarding's competitor search, optional). Onboarding also uses two bindings, not secrets — Workers AI (AI) and Browser Rendering (BROWSER) — both remote: true in wrangler.jsonc, so local dev proxies to the real services and the account needs both enabled.

• bun run check — typecheck · bun run lint / lint:fix — Biome · bun test — unit tests
• bun run build — production build · bun run deploy — build + wrangler deploy

Self-host

wrangler queues create refd-ingest && wrangler queues create refd-ingest-dlq
wrangler secret put JWT_SECRET
wrangler secret put BRIGHTDATA_API_TOKEN
wrangler secret put ADMIN_EMAILS       # comma-separated admin/operator allowlist
wrangler secret put EXA_API_KEY        # optional: onboarding competitor search
bun run db:migrate:remote
bun run deploy

You'll need a Cloudflare account (Workers paid plan for Queues, plus Workers AI and Browser Rendering enabled for onboarding), a D1 database + R2 bucket (ids/names in wrangler.jsonc), and a BrightData account: fill the dataset IDs in wrangler.jsonc vars (dashboard → Web Scrapers → each AI scraper) and create a SERP API zone matching BRIGHTDATA_SERP_ZONE. Set SCHEDULED_MONITORING_POLICY to all for a self-hosted deployment; the checked-in entitled policy is for refd.ai and limits cron to active pilot or subscribed workspaces. Cron schedule (daily 06:00 UTC), samples, and geo also live in wrangler.jsonc.

Notes

• AI answers are non-deterministic: SAMPLES=2 per prompt/surface; read trends across runs, not single samples.
• Each standard full run is capped at 25 active prompts × 3 enabled surfaces × samples (25 × 3 × 2 = 150 records at the default). Quota scales with the number of workspaces eligible for scheduled monitoring.
• Design system: docs/DESIGN.md. Original implementation plan (historical): docs/plan.md.

Contributing

Contributions welcome. See CONTRIBUTING.md for setup and the checks your PR must pass, and CODE_OF_CONDUCT.md for community expectations. Found a security issue? Follow SECURITY.md instead of opening a public issue.

License

MIT © refd