Apify

Apify AI

Apify AI

Apify AI

Apify AI

Apify AI

Apify AI

Apify AI

Apify AI

Apify AI

Apify AI

Built a morning brief agent on Apify that pulls from Slack, Gmail, Calendar, and Notion

I kept switching between apps every morning trying to figure out what actually needed my attention. Slack, Gmail, Google Calendar, Notion, two or three accounts each. I just wanted something that would tell me what matters. So I built an actor on Apify to see if it could work. It fetches everything, sends the raw data to Claude via the Anthropic API, and posts the brief to Slack. Took a few iterations to get the prompt right but it genuinely gets the job done now. What I liked: it fits within Apify's $5 free plan limit, so zero ongoing cost to run it once a day. Two ways to use it: The simpler one: the actor fetches all data, calls the Anthropic API directly to generate the brief, and posts it to your Slack channel. Everything in one run. But you need to have Anthropic API key. The more flexible one: connect Claude to Apify via MCP or the API, schedule the actor to run every morning to prefetch and store the data, then have Claude read it and generate the brief on demand. Useful if you want to ask follow-up questions or regenerate without waiting for another full crawl. Live on the Apify Store if anyone wants to try it. Glad for any feedback. submitted by /u/AmbiguousSun [link] [comments]

I got sick of rebuilding the same ad research pipeline for every new client so I built something that just handles it

I got sick of reconfiguring a new stack of tools every time I took on a new app client. The workflow was always the same. Open Ad Library, find what's running, screenshot the good stuff, set up Apify, connect Airtable, wire up the pipeline, brief an editor, wait a week. Then do it all again for the next client. Tried building my own pipeline. Claude Code, Apify, Airtable, Whisper, n8n. Spent more time maintaining the infrastructure than actually running ads. So I built Zura instead. Paste any Meta Ad Library URL. It analyzes the winning creative and generates launch-ready video variations. No pipeline. No setup per client. No tooling to maintain. The time between "found a winner" and "launched a test" went from days to minutes. zura.today submitted by /u/Natural-Ad7262 [link] [comments]

Claude for Cybersecurity tasks

Just some ways in which I use Claude for cybersecurity work. Prioritizing Vulnerabilities: By uploading scan reports, asset lists, and using the Model Context Protocol (MCP), Claude can analyze and prioritize critical findings, determine patching sequences, and suggest timelines. Building Proposals: Input instructions, company collateral, and RFPs within a Claude Project to generate high-quality, succinct project proposals in minutes. Lately, I've begun using Claude Design to prepare the actual decks. Summarizing News: Claude Cowork to run a daily task that summarizes cybersecurity news of the day. Creating Threat Intel Reports: When provided with details on a breach or threat, Claude can produce professional, validated threat intelligence reports that include Indicators of Compromise (IOCs), attack chains mapped to the MITRE framework, and detection logic. Bulk Document Review: Claude Code in a specific folder, to process large quantities of documents, such as résumés for an open position. Developing Security Toolkits: Claude Code can act as a partner in building comprehensive security and compliance toolkits for environments like AWS and Azure, while helping document engineering principles and best practices. Scraping for Content Ideas: Using the Apify MCP, Claude can scrape platforms like YouTube, Reddit, and Instagram to identify trending topics in cybersecurity and AI. Automated Penetration Testing: Using open-source pentesting repositories, Claude Skills can perform thorough, authorized penetration tests against specific systems and generate comprehensive reports in a short amount of time. Acting as a Learning Guide: Claude can create personalized study programs and roadmaps, recommending relevant white papers, researchers, and practical projects based on the user's available time to help them master new topics. Filling Security Questionnaires: Claude can assist in completing long, tedious customer security checklists by leveraging previous scan results, risk registers, and security policies to provide accurate, evidence-based answers. A video where I demo these use cases is in the first comment. What are some ways in which you use Claude - or other AI tools - in your day-to-day cybersecurity work? submitted by /u/AnswerPositive6598 [link] [comments]

I built cold sales pipeline for Claude Code that launches a full campaign from one prompt

Been using Claude Code for B2B cold outreach at our agency (20+ people on the team, all of them use this daily now). We built a set of skills to solve a pretty annoying problem: our reps juggle anywhere from 5 to 10 tools per campaign. Prospecting in one tab, enrichment in another, scraping in a third, sequences somewhere else. Every campaign starts with a couple hours of this manual assembly before a single email goes out. So basically what happens: you run one command with your company website + short description of who you're going after, and Claude handles the rest. like /launch gtm-mcp.com fintech startups 10mln+ MRR in the US Builds Apollo filters, runs the search, scrapes each company's site, decides whether they actually fit your ICP (with reasoning you can read - this part alone throws out like 60-70% of Apollo results that look right in the list but obviously don't match once you actually look at the website), finds decision makers, writes the sequence, pushes it all into SmartLead in draft. You check it at two points, approve, done. it's 13 skills plus API around Apollo, Apify and SmartLead. Everything runs locally on your machine, you plug in your own API keys, nothing touches our servers, there aren't any servers on our side to touch. I'll be honest about what it doesn't do because I'm tired of the "AI 10x'd my outreach" posts: it won't fix your reply rates by itself. You still need to know who you're targeting and you still need to look at the sequences and fix whatever sounds off. The actual win is that the 5-10 tool juggling act per campaign just disappears. Same output, less time spent being a human copy-paste machine between tabs. Would really appreciate any honest takes, even brutal ones. this is completely open source and free, no hidden paywalls GitHub: https://github.com/impecablemee/gtm-mcp Instruction how to use: gtm-mcp.com submitted by /u/decaster3 [link] [comments]

I built a free claude blog skill that actually studies your business, researches competitors & keywords to find winning blog topics and high-quality articles with infographics, internal linking, product promotion, and more...

Most AI writing tools are a fancy wrapper around "give me 1500 words about X." They don't know your business, your competitors, what's already ranking, or why someone would read your article over the 10 that already exist. The output is always that same slightly-hollow, over-structured content that reads like it was written by someone who's never actually done the thing they're writing about. I wanted to build something that approached content strategy the way a good SEO consultant would like studying the business first, doing real research, then writing So I built a set of Claude Code slash commands that run a full pipeline. Here's what it actually does: Step 1: Onboarding Scrapes your website, extracts a structured business profile (product type, ICP, differentiator, brand voice, integrations), then hits DataForSEO's SERP API to find your 3 direct competitors. Everything gets saved locally in .claude/blog-config.json. You run this once. Step 2: Site Intelligence (the interesting one) This is where it gets serious. It runs three keyword sources in parallel: Your existing rankings (top 100 by traffic value from DataForSEO) Competitor keywords (top 200 per competitor) Seed expansion: Claude Haiku generates 30 seed phrases based on your ICP's pain points and integrations, then DataForSEO expands each seed into ~30 related keywords (30 parallel API calls), then bulk KD lookup on all of them That's roughly 2,000 raw keywords before dedup. After merging and deduplicating, it filters by volume floor, KD ceiling relative to your domain rating, and strips anything you already rank top-5 for Then Claude Haiku classifies every remaining keyword into TOFU/MOFU/BOFU in parallel batches of 50. Claude Sonnet groups them into 6–10 topical clusters. Each cluster gets a pillar keyword and supporting keywords. Opportunity scoring uses a weighted additive formula (not multiplicative since it compresses everything toward zero): score = (0.40 × log_volume + 0.40 × difficulty + 0.20 × funnel) × 100 Volume is log-normalized against a 100k anchor so a 1,000/mo keyword scores 60% instead of 1%. 70+ means actually worth targeting. It picks one topic per cluster (breadth-first), generates SEO titles for all 10, and saves them to your content pipeline. Step 3: Content Engine Per article, it runs: DataForSEO advanced SERP for the target keyword → Firecrawl scrapes the top 3 ranking articles to extract H2 structure and avg word count Tavily batch search: 3 queries in parallel for recent news, expert opinions, common mistakes YouTube Data API → transcript extraction via Apify → Claude Haiku pulls 2 concrete insights Then Claude Haiku does SERP gap analysis like what are all 3 top articles covering, what are they missing, what's the best featured snippet opportunity. Claude Sonnet generates a full outline: every H2, H3, word count per section, where research gets placed, where the product mention goes (with specific framing instruction), image positions, CTA matched to funnel stage. Then Claude Sonnet writes the full article in one shot against that outline. Images get generated after Haiku reads the actual written content to create better DALL-E prompts than you'd get from just the keyword. Schema markup and meta assets are separate Haiku calls. Product plug is deliberately constrained: one mention, at a designated section, only after the reader has felt the pain it solves. No marketing language. The outline specifies the exact framing. Output is a folder: article.md (pure content, copy into CMS), publish-kit.md (meta, schema JSON, publishing checklist), and images/. The whole thing is Claude Code slash commands - /blog-onboard, /blog-topics, /blog-write. You run them in any project directory. All data stays local. I open-sourced it here: github.com/maun11/claude-blog-engine It's working but honestly there's a lot of room to improve it. If you've built anything in this space or have opinions on the architecture, would genuinely appreciate the feedback. And if you improve something, PRs are welcome and there's a lot of low-hanging fruit in the pipeline script (scripts/topics_pipeline.py) specifically. submitted by /u/Visible-Mix2149 [link] [comments]

What is the best way to capture online mentions and capture signals daily?

I was talking with a friend who works in a startup and they would like to track decision makers across a specific set of companies and be updated daily. News mentions, comments or signals from those people across the web, and social media, particularly X. What is the best way to achieve this? A custom solution made with Claude code, leveraging scrapers (Ex. Firecrawl, Apify)? Or would n8n and similar platforms be better? Any personal experiences with this? Thanks! submitted by /u/W0rldIsMy0yster [link] [comments]

Apify not getting installed

This error is showing. What to do? submitted by /u/Distant_aura [link] [comments]

using Claude Code for go-to-market, not just code. context engineering patterns that keep sessions productive.

most posts here are about coding with Claude. I use Claude Code for something different: running an entire go-to-market operation. scraping. enrichment. databases. email infrastructure. content across 5 platforms. sharing what works because the patterns apply to any non-coding use case. the rate limit problem is a context problem two people on my team use Claude Code full-time. one builds the product. I build the GTM machine around it. neither of us hit rate limits regularly. three things that made the difference: CLAUDE.md file at the project root. Claude Code reads it automatically every session. project context, file paths, workflow rules. 15 lines. the agent knows what it's working with before you say anything. eliminates the repetitive "here's my project" preamble that burns context every session. scope your sessions. I cd into the specific repo and subdirectory before starting. Claude Code reads the local CLAUDE.md and surrounding files. smaller scope = less context consumed = more useful output per session. CLI tools instead of MCP servers where possible. MCP tool definitions load into your system prompt and consume tokens whether you call them or not. a CLI tool takes zero context. Claude Code just runs bash commands. Apify, Supabase, gcloud all have CLIs. I went from 15 MCP servers to 3. subagents for the heavy lifting anything that involves reading a lot of files or exploring a codebase goes to a subagent. the subagent burns through its own context window. reports back a summary. main session stays clean and focused. batch operations, research, file analysis. all subagents. main session coordinates and directs. what I actually run through Claude Code daily - Apify CLI to scrape competitor follower lists. 10K followers for about $5. cross-reference multiple scrapes to find companies evaluating solutions in your space. - Python scripts calling Apollo API for enrichment. 0-credit endpoints for company data and job-change detection. 27K contacts processed with resumable caching. - Supabase CLI for database operations. push scraped and enriched data. query in natural language through Claude Code. - Google Sheets sync so non-technical teammates see a spreadsheet, not a terminal. - content drafting with voice DNA files loaded as context. anti-slop rules catch AI-sounding patterns before publishing. - 12 email domains managed through Azure Communication Services. warm-up cron jobs running automatically. all from terminal sessions on a Mac Mini. Claude Code reads the project structure, knows the schemas, knows the voice rules, and executes. I direct. what doesn't work loading every MCP integration you can find. your sessions will crawl. long exploratory sessions without subagents. context fills up. output quality drops. session becomes useless after 30 minutes of heavy file reading. generic prompts at the home directory level. "help me with my business" gives you generic output. "cd into this repo, read the CLAUDE.md, and run the enrichment script on this CSV" gives you results. skills bloat. 40 custom slash commands means 40 tool definitions in context. most of them you'll never use in a given session. keep it lean. the skills that matter are the ones you actually use weekly. open sourced the patterns github.com/shawnla90/gtm-coding-agent 10 chapters. context engineering. token efficiency. CLI vs MCP vs API decision framework. local-first GTM infrastructure. terminal multiplexing. working Apify and Apollo scripts with docs. MIT licensed. built for GTM use cases but the context engineering and session management patterns apply to any Claude Code workflow. submitted by /u/Shawntenam [link] [comments]

I built a skill that gives Claude Code access to every major social platform: X, Reddit, LinkedIn, TikTok, Facebook, Amazon

Was tired of my agent not being able to pull real data from social platforms. Every time I needed tweets, Reddit posts, or LinkedIn profiles, I'd either scrape manually or stitch together 5 different APIs with different auth flows. So I built Monid, a CLI + skill that lets your agent discover data endpoints, inspect schemas, and pull structured data from platforms like X, Reddit, LinkedIn, TikTok, Facebook, and Amazon. How it works with Claude Code Just tell Claude Code: "Install the Monid skill from https://monid.ai/SKILL.md" Then your agent can: ```bash Find endpoints for what you need monid discover -q "twitter posts" Check the schema monid inspect -p apify -e /apidojo/tweet-scraper Run it monid run -p apify -e /apidojo/tweet-scraper \ -i '{"searchTerms":["AI agents"],"maxItems":50}' ``` The agent handles the full flow — discover → inspect → run → poll for results. What's supported X/Twitter (posts, profiles, search) Reddit (posts, comments, subreddits) LinkedIn (profiles, company pages) TikTok (videos, profiles, hashtags) Facebook (pages, posts) Amazon (products, reviews) More being added Would love feedback from anyone who tries it. What platforms or data sources would be most useful for your workflows? submitted by /u/Shot_Fudge_6195 [link] [comments]

Cowork scheduled tasks not accessing MCP connectors - is this a known limitation?

I've been trying to automate a weekly job scraping task using Cowork's scheduled tasks feature, with Apify connected via MCP to do the actual scraping. I'm hitting a wall and can't tell if this is a bug, a limitation, or something I'm configuring wrong. What works: Apify is connected and works fine in interactive Cowork tasks. If I start a manual task and ask it to use Apify, it calls the actor, retrieves results, and writes them to a file without issues. No problems there. What doesn't work: When the same instructions run as a scheduled task, Cowork searches for connectors and finds none. The log shows literally "0 connectors / No connectors found," so it falls back to web search instead. Apify is never called and no credits are used. What I've already tried: - All Apify tool permissions are set to Always Allow - Deleted and recreated the scheduled task - Run the scheduled task manually using Run Now — no approval prompts appear, it just skips Apify entirely - Checked the Anthropic support docs, which say connectors should be available in scheduled tasks The support doc (https://support.claude.com/en/articles/13854387-schedule-recurring-tasks-in-cowork) says scheduled tasks have access to the same capabilities as regular Cowork tasks including connected tools. That doesn't appear to be the case in practice. Has anyone got MCP connectors working in a scheduled task? Is there a setup step I'm missing, or is this a known issue? submitted by /u/twiddle1977 [link] [comments]

The developer settings on claude desktop won't open

I'm trying to edit config in claude desktop so i could add a few apify actors but everytime i try to open the developer config file this pops up, what do i do?? submitted by /u/Cultural-Fondant-281 [link] [comments]

Made some MCP tools for e-commerce research, figured this crowd might find them useful

I've been using Claude heavily for e-commerce research and kept running into the same problem, getting it to pull real competitive data meant either copy-pasting manually or writing custom code every time. I probably wasted 10 hours before realizing I was an idiot and could just make something to skip that step lol. So I built three MCP servers and put them on Apify so Claude can just call them directly. Shopify one lets Claude analyze any public store without needing an API key. You can ask it things like "what apps is Gymshark running" or "show me Allbirds' full product catalog with pricing" and it just works. Amazon one does product research with a scoring system I built that weights demand signals, competition level, price health, and BSR rank. So instead of getting a raw list of results you get each product scored on how good of an opportunity it actually is. Google Maps one finds local businesses by industry and location and scores them as sales leads. It also generates an outreach hint for each one based on what data signals drove the score — like "no website, offer web design" or "low rating, offer reputation management." All three are live now: • https://apify.com/rothy/shopify-intel-mcp • https://apify.com/rothy/amazon-intel-mcp • https://apify.com/rothy/gmaps-intel-mcp Would be curious if anyone has ideas for other data sources that would be useful to add. submitted by /u/Rothy12 [link] [comments]

Solo branding agency lead gen?

I’m looking to use Claude as a lead gen tool. Currently I have a coworker task that is supposed to us apify to scrape Google Maps and give me a list of 10 businesses with no website and either an email address (using vibe prospector) or a social media handle I can contact but it works maybe half the time. Either Claude tells me apify isn’t connected or all the businesses it shows me have websites. Has anyone had luck in my specific use case (website/branding)? What did you do? I’m trying to lower the cost of entry as I have 0 client pipeline and reserving funds. submitted by /u/ianfgraphics [link] [comments]