Eval-backed discovery for the auxiliar.ai gateway — the best web-access provider per job, measured.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
💡 Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
Eval-backed tool discovery for AI agents, on the auxiliar.ai web-access gateway — one API key for 24 search, scraping, browser-automation and voice APIs, upstream keys injected server-side, usage at each provider's real metered price.
Ask it "what's the best provider for this job?" and it answers from measured public benchmarks — every provider runs the identical task corpus per verb; scorecards carry their run dates; weak scores are published, not hidden.
or in any MCP client config:
| Tool | What it does |
|---|---|
recommend_tools | Best provider(s) for a job (search, scrape, crawl, extract_ai, extract_rules, answer, screenshot, scrape_domain, act, act_agent, serp, parse, watch), ranked by measured quality/latency/cost/errors. Optional optimize_for, max_latency_ms, max_cost_usd, limit. |
get_scorecard | The full leaderboard for one verb — every scored provider, raw metrics, run dates. |
get_provider | One provider in full: route, pricing, choose/avoid guidance, all its dated scorecards. |
about_auxiliar | What the gateway is, how to get a key, how to call it. |
Every response carries the run date behind each number (measured_on, latest_run), the ranking context (rank #n of m), honest caveats, providers excluded_by_constraints (never silently dropped), and gated_not_scored entries for providers that couldn't be scored on the shared corpora.
Recommendations return an executable call pattern:
Same paths, parameters and responses as each provider's own docs — the gateway injects the upstream key server-side. Get a key (with $5 free credit, no card) at auxiliar.ai.
Benchmark data loads at runtime from auxiliar.ai/evals.json (1h in-memory cache) and falls back to a bundled snapshot offline — responses declare which via data_source. The same data renders the human-readable scorecards at auxiliar.ai/tools. Rankings carry no house incentive: the gateway's fee is flat at credit top-up, so nothing is earned by steering you toward pricier providers.
Releasing: bump the version in package.json and server.json (two spots) — npm run check-versions (run automatically at prepublish) enforces sync — then npm publish and mcp-publisher publish.
web_search, scrape, extract, crawl, …), routed by the same measured rankings.MIT
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