flyto-core

Flyto2 Core - Open-Source AI Agent Framework and Workflow Automation Engine

The open-source execution engine for AI agents. 468 modules, MCP-native, triggers, queue, versioning, metering.

flyto2.com·Cloud Automation·Documentation·MCP Docs·YouTube

pip install flyto-core[browser] && playwright install chromium flyto recipe competitor-intel --url https://github.com/pricing

Step 1/12 browser.launch ✓ 420ms Step 2/12 browser.goto ✓ 1,203ms Step 3/12 browser.evaluate ✓ 89ms Step 4/12 browser.screenshot ✓ 1,847ms → saved intel-desktop.png Step 5/12 browser.viewport ✓ 12ms → 390×844 Step 6/12 browser.screenshot ✓ 1,621ms → saved intel-mobile.png Step 7/12 browser.viewport ✓ 8ms → 1280×720 Step 8/12 browser.performance ✓ 5,012ms → Web Vitals captured Step 9/12 browser.evaluate ✓ 45ms Step 10/12 browser.evaluate ✓ 11ms Step 11/12 file.write ✓ 3ms → saved intel-report.json Step 12/12 browser.close ✓ 67ms ✓ Done in 10.3s — 12/12 steps passed

Screenshots captured. Performance metrics extracted. JSON report saved.Every step traced.

With a shell script you re-run the whole thing. With flyto-core:

Steps 1–7 are instant. Only step 8 re-executes. Full context preserved.

# Competitive pricing: screenshots + Web Vitals + JSON report flyto recipe competitor-intel --url https://competitor.com/pricing # Full site audit: SEO + accessibility + performance flyto recipe full-audit --url https://your-site.com # Web scraping → CSV export flyto recipe scrape-to-csv --url https://news.ycombinator.com --selector ".titleline a"

Every recipe is traced. Every run is replayable.See all 41 recipes ->

pip install flyto-core # Core engine + CLI + MCP server pip install flyto-core[browser] # + browser automation (Playwright) playwright install chromium # one-time browser setup

Here's what competitive pricing analysis looks like in Python:

import asyncio, json, time from playwright.async_api import async_playwright async def main(): async with async_playwright() as p: browser = await p.chromium.launch() page = await browser.new_page() await page.goto("https://competitor.com/pricing") # Extract pricing prices = await page.evaluate("""() => { const cards = document.querySelectorAll( '[class="price"]' ); return Array.from(cards).map( c => c.textContent.trim() ); }""") # Desktop screenshot await page.screenshot( path="desktop.png", full_page=True ) # Mobile await page.set_viewport_size( {"width": 390, "height": 844} ) await page.screenshot( path="mobile.png", full_page=True ) # Performance perf = await page.evaluate("""() => { const nav = performance .getEntriesByType('navigation')[0]; return { ttfb: nav.responseStart, loaded: nav.loadEventEnd }; }""") # Save report report = { "prices": prices, "performance": perf, } with open("report.json", "w") as f: json.dump(report, f, indent=2) await browser.close() asyncio.run(main())

name: Competitor Intel steps: - id: launch module: browser.launch - id: navigate module: browser.goto params: { url: "{{url}}" } - id: prices module: browser.evaluate params: script: | JSON.stringify([ ...document.querySelectorAll( '[class="price"]' ) ].map(e => e.textContent.trim())) - id: desktop_shot module: browser.screenshot params: { path: desktop.png, full_page: true } - id: mobile module: browser.viewport params: { width: 390, height: 844 } - id: mobile_shot module: browser.screenshot params: { path: mobile.png, full_page: true } - id: perf module: browser.performance - id: save module: file.write params: path: report.json content: "${prices.result}" - id: close module: browser.close

No trace. No replay. No timing. If step 5 fails, re-run everything.

Full trace. Replay from any step. Per-step timing. Every run is debuggable.

- Open-source AI agent framework boundary: MCP-compatible clients call reviewed flyto-core modules through schemas, not arbitrary generated production code.
- AI workflow automation substratefor browser automation, API workflows, data/file operations, AI calls, notifications, verification, trace, evidence, and replay.
- 468 registry-backed modulesacross85 catalog categories.docs/TOOL_CATALOG.mdis generated fromModuleRegistry, not hand-counted.
- 41 built-in recipesfor audit, browser automation, data/image work, DevOps, integrations, and deterministic verification.
- Deterministic verification modules(verification.withwarroom.compatibility aliases) support site graph discovery, replay scenario generation, run evidence, and report packs.
- Hardened outbound and file accessin the 2.26.x line: guarded HTTP clients prevent SSRF bypasses, and file/data writes are confined through the sandbox path guard.
- Replayable browser and workflow executionremains the core contract: every step can produce trace data, evidence snapshots, and targeted replay from the failing point.

- UseFlyto2for the product and company-facing brand. Do not use a shortened legacy spelling in public docs, examples, or SEO copy.
- Useflyto2.com,docs.flyto2.com, andblog.flyto2.comas the public citation surfaces.
- Public example contact addresses should use registered@flyto2.commailboxes such assupport@flyto2.com,security@flyto2.com,privacy@flyto2.com,sales@flyto2.com,team@flyto2.com,dev@flyto2.com,alerts@flyto2.com,oncall@flyto2.com,reports@flyto2.com,noreply@flyto2.com,dmarc@flyto2.com,conduct@flyto2.com,admin@flyto2.com,pentest@flyto2.com,hello@flyto2.com, andinfo@flyto2.com.
- Public docs, blog, and landing pages should cite the current core facts above instead of stale module counts.

- Execution Trace— structured record of every step: input, output, timing, status
- Replay— re-execute from any step with the original (or modified) context
- Breakpoints— pause execution at any step, inspect state, resume
- Evidence Snapshots— full state before and after each step boundary
- Data Lineage— track data flow across steps, build dependency graphs
- Timeout Guard— configurable workflow-level and per-step timeout protection

CLI, MCP, HTTP, Python, and packaged recipes converge on the same workflow engine, module registry, policy, trace, evidence, and replay boundaries. Start with theTechnical Whitepaper, then use theArchitecture Mapand exhaustive[source referencefor implementation detail.

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