Apify

YOUR AI AGENT SHOULD BE ABLE TO FIND ITS OWN TOOLS Want it to gather useful data for your next project? > restaurants with ratings and opening hours > product prices from Amazon > fresh content from the web Getting that data usually means finding the right integration, understanding its inputs and connecting it to your workflow. @Apify's MCP server lets your agent handle the tool discovery 💥 ONE connection gives it access to a marketplace of thousands of ready-to-run tools. You just describe the job in plain English. The agent can then find a suitable tool, configure it, run it and retrieve structured results 🙌 You don't have to know the tool's name before you ask. There's a smart detail here, too! tools are discovered on demand, so the entire catalog doesn't need to be loaded into context upfront. A broad toolbox with a small starting footprint. here's how the pieces fit together 🧵↓

Estoy viciadísimo a los Actors de Apify y ahora veo ideas por todos lados El otro día hablando con mi tía que dirige una pequeña red de gasolineras me puse a investigar y he creado una API con los precios diarios de 11k de todo el país. Luego me calenté y cree un directorio SEO que se actualiza solo cada 3 horas tirando de mi Actor de Apify. Con su mapa, opción "cerca de mi", como llegar y toda la movida... quizás lo acabe convirtiendo en una app para probar. echadle un ojo crítico a ver que os parece, si veo que el proyecto tira iré poniendo actualizaciones en el Telegram os dejo abajo los links

running a company nowadays feels kinda dystopian my team is 50+ people in 12 countries, but i talk to my agents more than my human teammates - voice note to grokbot - mattpocock/skills /grill-me so the agent interrogates the idea before anything gets built - spec drops into linear through the linear mcp - exa + firecrawl agent reads every competitor site, pricing page and changelog - ideabrowser.com to find ideas and trends - apify pulls g2, reddit and app store reviews - prompt: "find the 10 complaints that show up most and quote the users" - context7 so the agent reads the latest docs before it touches any api the design - claude code + paper mcp - 4 versions of every screen before a single line of code - pick pieces from 2, it merges them. diverge then converge - frontend-design skill from anthropic/skills + our own design system skill - cleanshot screenshots of any ui i like go straight in with "make it feel like this" the build - pingdotgg/t3code as the control surface for every agent, from my phone too - stablyai/orca runs a fleet of agents in parallel, each in its own git worktree - graphify maps the whole codebase into a knowledge graph so agents navigate instead of guess - headroom compresses tool outputs before they hit the model, so tokens go 20-95% further - lsp plugins so the agent sees types and errors like an ide does - security guidance hook flags risky edits before they land - supabase mcp for the database, stripe for billing - github mcp opens the pr, vercel spins up a preview - loops run overnight, i check what shipped over coffee the user testing - lightpanda as the headless browser, way lighter than chromium so you can run hundreds at once - agents click every flow on the preview like a first-time user - one persona is impatient, one is confused, one is on a phone - playwright + chrome devtools mcp for regression tests the bugs - sentry mcp catches the error - agent reads the stack trace and opens a fix pr in under 10 minutes - human just approves the data - posthog mcp cron at 7am on yesterday's funnel - any step that drops more than 10%, the agent watches 20 session replays and tells me why - stripe mcp pulls every cancellation reason into one doc every monday the agents' tools - orgo so every agent gets its own computer - agentmail so every agent gets its own inbox - agentphone so i can call them from the car - composio connect-apps for every other connector - akitaonrails/ai-memory, a git-backed markdown wiki so they remember what we decided last week the skills - wshobson/agents so skills work across claude code, codex and opencode - my writing voice - our design system - how we write specs - skill creator so the agents write new skills themselves some helpful tricks - one agent per platform. the x agent never touches email - cheap model for triage, opus for anything that ships - every output gets scored 1-10 by an llm judge. under 8 goes back - every agent writes a 5-line log at night so i can read the whole company in 2 minutes - every agent mistake becomes a new skill, so it only happens once the team - humans get version 5, not my voice note which they are happy about lol - their job is creative feedback, relationships and telling the agents what they got wrong a human pm reviews the funnel once a week. this reviews it every morning running a company is now voice notes and inference