The entire web is your database
Describe the data you need. The agent builds the pipeline. Any website becomes structured, queryable data — flowing into your databases on schedule.
The web wasn't built for machines
From description to database
Describe what you need
Plain English or YAML. "I need decision makers at Series B SaaS companies and their recent LinkedIn activity."
Agent discovers and builds
Finds endpoints, chains data sources, estimates cost. You approve — it runs.
Data flows into your database
Structured JSON into SQLite, PostgreSQL, or ClickHouse. Auto-schema. LLM enrichment built in.
Refreshes on schedule
One cron expression. Incremental tracking. Webhook on completion.
name: prospect-pipeline sources: target_companies: endpoint: /api/linkedin/search/companies input: industry: "SaaS" employee_count: "51-200" parallel: 3 decision_makers: endpoint: /api/linkedin/company/employees depends_on: target_companies input: company: ${target_companies.urn} keywords: "VP Sales, Director Sales" count: 5 on_error: skip recent_posts: endpoint: /api/linkedin/user/posts depends_on: decision_makers input: urn: ${decision_makers.internal_id.value} count: 5 storage: format: parquet path: ./data/prospects
You: "I need decision makers at Series B SaaS companies and their recent LinkedIn activity" Agent: Discovering endpoints... Building pipeline: companies → employees → posts Estimated cost: ~2,400 credits Proceed? [y/n] Agent: Collecting companies (47 found)... Mapping to employees (312 contacts)... Fetching post history... Storing in Parquet → ./data/prospects/ Done. 312 records. Query with: anysite dataset query pipeline.yaml
Pre-built where it matters. AI-powered for everything else.
Profiles, companies, posts, jobs, messaging. Read + write.
Twitter / X
Profiles, tweets, threads, search, followers.
Posts, reels, comments, followers.
Subreddits, posts, comments, user history.
YouTube
Videos, channels, comments, subtitles.
SEC EDGAR
10-K, 10-Q, 8-K filings.
GitHub
Repos, profiles, code metadata.
Amazon
Products, reviews.
Search, Maps, News.
Any URL
AI parser. Any web page → structured JSON.
What teams build with this
Prospect databases that refresh overnight
Define ICP in YAML. Pipeline runs nightly. CRM stays current.
Track competitors across every signal
Monitor LinkedIn, Twitter, Reddit, YouTube. Diff between runs.
10,000 records, zero extraction code
Batch + parallel + incremental. LLM enrichment built in.
Give your agents reliable data access
Structured JSON, consistent schemas, agent-native protocol.
1,000 tokens, not 50 million
Scales with data size
Same cost at 10 or 100K records
One engine, four interfaces
MCP to explore. CLI to execute. Same engine underneath.
Explore data conversationally
Plain English queries via Claude, Cursor, or ChatGPT. 60+ tools. No code required.
Connect via MCP →Production pipelines from your terminal
YAML workflows, batch processing, database loading, LLM enrichment, cron scheduling. pip install anysite-cli
Integrate into your applications
85+ endpoints. Cursor pagination. Consistent JSON schemas.
API Reference →Start with MCP, scale with credits
MCP Unlimited
- Unlimited MCP requests (fair use: 50K/month)
- All 60+ MCP tools — LinkedIn, Twitter, Instagram, Reddit, YouTube, SEC EDGAR, and more
- Person Analyzer and Competitor Analyzer skills
- Works with Claude Desktop, Claude Code, Cursor, ChatGPT
- Rate limit: 6 requests/minute
Credit plans unlock the REST API and CLI at scale. All plans include MCP access and full platform coverage.
| Plan | Price/mo | Credits | Rate Limit | |
|---|---|---|---|---|
| Starter | $49 | 15,000 | 60 req/min | Start trial → |
| Growth | $200 | 100,000 | 90 req/min | Get started → |
| Scale | $300 | 190,000 | 150 req/min | Get started → |
| Pro | $549 | 425,000 | 200 req/min | Get started → |
| Enterprise | $1,199+ | 1.2M+ | 200 req/min | Contact us → |