goodnight000/api-anything

Goodreads stopped giving out API keys in 2020. Google Flights never had a public API. An agent that needs either one drives a browser: it clicks, waits, reads the screen, and pays for every step in time and tokens. API Anything learns the request the site's own page sends, once, and then calls it over plain HTTP. It shares what it learned, with every cookie and token stripped out, so the next agent gets JSON from one request.

Quick start

npx -y api-anything setup

Setup lists the agents it finds (Claude Code, Codex, Cursor, Claude Desktop, Gemini CLI, VS Code) and asks which to connect the MCP server and the skill to; --agents names them instead, and the always-on Hermes gateway is added only by name. Then it asks whether to help build the shared catalog. setup --local-only keeps everything on this machine. Node 22.13 or newer; no account, no API key. Or tell your coding agent: Set up API Anything for me: https://github.com/goodnight000/api-anything/blob/main/INSTALL.md. What setup changes, and every client

Restart the agent and ask it something like "What does Goodreads rate Piranesi?", or call an operation yourself:

npx -y api-anything call hacker-news search query=sqlite

{"ok":true,"class":"ok","tier":1,"data":[
  {"title":"Hosting SQLite databases on GitHub Pages or any static file hoster", ...}, ...],
 "ms":185}

tier: 1 means one plain HTTP request, with no browser and no account. A failure says what happened (class), why (reason) and what to do next (next).

Who's talking about your project

You shipped something. Is anyone talking about it? Finding out means five search pages, or five different APIs with their own keys, OAuth apps and client libraries. examples/mentions.mjs asks Hacker News, Reddit, YouTube, GitHub and Mastodon at once, from an empty home, with no account:

The core of it is six reads in parallel, each capped at plain HTTP:

import { call } from "api-anything";

const sources = [
  ["hacker-news", "searchByDate", { query: project }],
  ["hacker-news", "searchByDate", { query: project, type: "comment" }],
  ["reddit", "search", { query: project }],
  ["youtube", "search", { q: project, filter: uploaded }],
  ["github", "searchRepos", { q: `${project} created:>${sinceDay}` }],
  ["mastodon", "tagTimeline", { tag: project }],
];
const results = await Promise.all(sources.map(([site, op, args]) => call(site, op, args, { maxTier: 1 })));

Run it from a checkout after npm ci: node examples/mentions.mjs <project>, with --days 30 for a wider window or --json for every link, for a script or a cron job.

On 2026-11-06, five runs from empty homes took 1.8 to 2.0 s each, Node's start included. Every run found the same 65 mentions. YouTube, GitHub, Mastodon and both Hacker News searches answered over plain HTTP. Reddit served a JavaScript challenge every time, and the script reported it as blocked and kept the rest. Transcript and details

The race

Same agent, same prompt, started together. Left: it drives headless Chrome. Right: it calls API Anything's Google Flights operation.

1.5 to 2× sooner · about half the tokens · the same cost or less · 20 of 20 answers correct

_{Claude Opus 5.5 in Claude Code, 2026-09-28. Shown at 3× speed with no cuts; the timers show real elapsed time. MP4 · how it was recorded}

On 2026-10-31 the same comparison on two more sites gave medians of 22.3 s against 9.6 s (Netflix episodes) and 31.4 s against 18.1 s (IKEA store addresses), 20 of 20 answers correct. Each is one site, one model and a few runs. Method, raw numbers and limits

How it works

• Learn. A headless browser loads the page for two example inputs. What changed becomes a parameter, the rest is kept byte for byte, and cookies become references. No LLM is involved.
• Call. Send the request with Node's fetch. If the site blocks that, fetch from inside a browser page; as a last resort for a read, run the page and read its answer.
• Repair. When the answer stops fitting, take the version another install repaired, or re-learn and save only after a replay works. A call that can't be repaired returns an error, never someone else's data.

The whole idea in 49 seconds · replay, fallback and repair · design

Use it anywhere

• MCP over stdio, for any agent: find_sites, call_operation, learn_site and the other tools, which declare output schemas for clients that check results. Frameworks: Vercel AI SDK, LangChain.js, OpenAI Agents SDK.
• HTTP: api-anything serve answers REST, publishes an OpenAPI document at /openapi.json, and serves MCP at /mcp. It listens on loopback only and needs a token. docs/SERVE.md
• Python: pip install "git+https://github.com/goodnight000/api-anything#subdirectory=python" gives a Client that starts the server for you, tools for agent frameworks, and typed code generated from an operation's schema. docs/PYTHON.md
• TypeScript: import { call } from "api-anything", or api-anything/host for an agent host that only calls installed operations. CLI and library at a glance
• Watching: --changes reports what was added, removed or changed since the last call (name a watcher with --watch), --max-age answers from a recent result instead of asking the site again, and a site's request budget keeps a cron job at human volume. examples/watch.mjs
• No install: the catalog lets you try a few public operations (Wikipedia, Open Library, USGS earthquakes, NASA images) from their pages, or with curl: curl 'https://api-anything-registry.forth-site.workers.dev/v1/try/wikipedia/getSummary?title=SQLite'.

Teach it a new site

Over MCP, an agent calls learn_site with a page URL and three values: two to learn from, one to check with. The operation is replayed with no cookies, then shared. From a shell:

api-anything learn 'https://lobste.rs/domains/{domain}' \
  --args domain=github.com --args2 domain=arxiv.org --args3 domain=youtube.com

For pages that need clicks or typing, an agent with the skill proposes operations, waits for your approval, and builds them. One run built Goodreads search, book details, an author's books and reviews in 6.3 minutes for $1.19. Learning, step by step · the Goodreads run · 25 s recording

The shared catalog

reCAPTCHA digitized millions of books from words people typed anyway. The catalog does the same for the web with calls agents make anyway. A new operation goes live after installs on 2 other networks call it successfully, and a live one is replaced only when 3 or more networks see it fail. When a site changes, the first agent to repair the operation repairs it for everyone. A site's own MCP server or OpenAPI document shows up in search beside what agents learned.

114 sites and 323 read operations ship with the package, from Hacker News, Reddit, YouTube and GitHub to Google Flights, Goodreads, Airbnb, Amazon and Steam. They cover selected features, not whole sites. Every bundled site · how the catalog works

Safety and what leaves your machine

• Calls run here, on your machine, network and sessions. The catalog never proxies your calls; a few public operations can be tried from the catalog page.
• Secrets stay home. A spec holds cookie:name, never the cookie, and a spec carrying a live credential can't be saved. Sessions are encrypted at rest with the OS keychain. login imports a site's cookies from the browser you already use, so there is usually no password to type.
• Writes are off unless allowed, sent once, refused as duplicate if repeated, and reported applied only when a read finds the result. No write operation is bundled. Every write guard

What leaves your machine

A search sends its words, domain or URL to the catalog, which keeps no search words. With sharing on, operations learned from public pages are shared, and so are repairs and reports (the version, the outcome, the tier and the time; never your arguments or data). An operation learned signed in goes only after you say yes, or once 3 installs on 3 networks learned the identical thing. Background verification of new operations is a separate question, and its default is no. With sharing off, or with --local-only, nothing is shared or reported. In full, with what the gate checks

Limits

It knows only the operations someone taught it, and the catalog is young. An operation that works for others can still fail for you (another region, a block on your network: Reddit challenges plain HTTP from many). There's no CAPTCHA solving; a challenge that doesn't clear is reported as blocked. Read each site's terms: you're responsible for how you use it. All limits

Help build it

Install it and leave sharing on: your agent's ordinary calls verify and repair operations for everyone. Learn a site from the list of domains agents asked for on the catalog's home page. Or add a spec to sites/ by pull request: Contributing has the rules and the dev commands.

Docs

doc	what's in it
Setup for agents	install, connect each client, learning, timeouts, troubleshooting
Reference	the CLI and library, results, creating operations, repair, logging in, safety, sites, limits
HTTP server · Python	api-anything serve; the Python package
Frameworks · Agent hosts	MCP from agent frameworks; the call-only host API
Design · Catalog	the authoritative spec and its reasons; how the catalog promotes, stores and trusts
Benchmark · Demos	how every number here was measured; recorded runs with transcripts and tapes
Contributing · MIT license	add a site spec, run the checks

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