Flyto2 Core

AI said it finished. Flyto2 shows the proof.

A Python execution engine for AI agents. It runs browser and API work as explicit steps, records what every step did, and replays from the step that failed — instead of re-running the whole job.

The current public inventory is 480 registry-backed modules across 88 catalog categories, including triggers, queue modules, workflow versioning, metering hooks, browser automation, API calls, data transforms, verification, files, and crypto.

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

flyto-core demo: API pipeline → replay → browser automation

Try it in 30 seconds

Terminal

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

Code

  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.

What happens when step 8 fails?

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

bash

flyto replay --from-step 8

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

How is this different?

	Playwright / Selenium	Shell scripts	flyto-core
Step 8 fails	Re-run everything	Re-run everything	`flyto replay --from-step 8`
What happened at step 3?	Add print(), re-run	Add echo, re-run	Full trace: input, output, timing
Browser + API + file I/O	Write glue code	3 languages	All built-in
Share with team	"Clone my repo"	"Clone my repo"	`pip install flyto-core`
Run in CI	Wrap in pytest/bash	Fragile	`flyto run workflow.yaml`

3 recipes to try now

bash

# 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 ->

Install

Terminal

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

Write Your Own Workflows

Recipes are just YAML files. Write your own:

yaml

name: price-monitor
steps:
  - id: open
    module: browser.launch
    params: { headless: true }

  - id: page
    module: browser.goto
    params: { url: "https://competitor.com/pricing" }

  - id: prices
    module: browser.evaluate
    params:
      script: |
        JSON.stringify([...document.querySelectorAll('.price')].map(e => e.textContent))

  - id: save
    module: file.write
    params: { path: "prices.json", content: "${prices.result}" }

  - id: close
    module: browser.close

bash

flyto run price-monitor.yaml

Every run produces an execution trace and state snapshots. If step 3 fails, replay from step 3 — no re-running the whole thing.

Usage

CLI — run workflows from the terminal

bash

# Run a built-in recipe
flyto recipe site-audit --url https://example.com

# Run your own YAML workflow
flyto run my-workflow.yaml

# List all recipes
flyto recipes

MCP Server — for Claude Code, Cursor, Windsurf

Terminal

pip install flyto-core
claude mcp add flyto-core -- python -m core.mcp_server

Or add to your MCP config:

config.json

{
  "mcpServers": {
    "flyto-core": {
      "command": "python",
      "args": ["-m", "core.mcp_server"]
    }
  }
}

Your AI gets all 480 modules as tools.

HTTP API — for integrations and remote execution

Terminal

pip install flyto-core[api]
flyto serve
# ✓ flyto-core running on 127.0.0.1:8333

Endpoint	Purpose
`POST /v1/workflow/run`	Execute workflow with evidence + trace
`POST /v1/workflow/{id}/replay/{step}`	Replay from any step
`POST /v1/execute`	Execute a single module
`GET /v1/modules`	Discover all modules
`POST /mcp`	MCP Streamable HTTP transport

Python API — for programmatic use

server.ts

import asyncio
from core.modules.registry import ModuleRegistry

async def main():
    result = await ModuleRegistry.execute(
        "string.reverse",
        params={"text": "Hello"},
        context={}
    )
    print(result)  # {"ok": True, "data": {"result": "olleH"}}

asyncio.run(main())

480 Modules, 88 Catalog Categories

Category	Count	Examples
`browser.*`	54	launch, goto, click, evaluate, screenshot, performance, challenge
`flow.*`	24	switch, loop, branch, parallel, retry, circuit breaker, rate limit
`array.*`	15	filter, sort, map, reduce, unique, chunk, flatten
`api.*`	13	OpenAI, Anthropic, Gemini, Notion, Slack, Telegram
`data.*`	13	JSON, YAML, CSV, XML parse/generate/convert
`string.*`	11	reverse, uppercase, split, replace, trim, slugify, template
`ai.*`	10	chat, model calls, vision, embeddings, moderation
`object.*`	10	keys, values, merge, pick, omit, get, set, flatten
`testing.*`	10	assertions, scenarios, E2E steps, reports
`image.*`	9	resize, convert, crop, rotate, watermark, OCR, compress
`verify.*`	9	evidence, visual diff, rulesets, annotations
`file.*`	8	read, write, copy, move, delete, exists, edit, diff
`stats.*`	8	mean, median, percentile, correlation, standard deviation
`test.*`	8	API, browser, and visual checks
`check.*`	7	validation and guard checks
`crypto.*`	7	AES encrypt/decrypt, JWT create/verify, hashes
`http.*`	7	get, request, batch, paginate, session
`validate.*`	7	email, url, json, phone, credit card
66 more prefixes	221	Docker, archive, math, k8s, network, PDF, AWS, cache, git

See the Full Module Catalog for every module, parameter, and description.

Engine Features

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

Architecture

CLI, MCP, HTTP, Python, and packaged recipes converge on the same workflow engine, module registry, policy, trace, evidence, and replay boundaries. Start with the Technical Whitepaper, then use the Architecture Map and exhaustive source reference for implementation detail.

Where to go next

You want to	Go to
Run one of the other built-in recipes	docs/RECIPES.md
Browse every module and parameter	docs/TOOL_CATALOG.md
See the module categories at a glance	480 Modules, 88 Catalog Categories
Configure network, filesystem, auth, and permission switches	docs/CONFIGURATION.md
Install a module pack or plugin	docs/PLUGIN_SDK.md
Write your own module	docs/MODULE_SPECIFICATION.md
Understand why the engine is shaped this way	docs/WHY.md
Read the product boundary between the three packages	ARCHITECTURE.md

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Testing

bash

python -m pytest
python -m ruff check .
flyto recipe full-audit --url https://example.com

Security

Report security vulnerabilities via security@flyto2.com. See SECURITY.md for the security policy and the environment variables that define the filesystem and outbound-network boundaries.

SECURITY_STATUS.md lists every published advisory with its severity, affected range, fixed-in version, and the regression test that covers it. Two boundaries are enforced registry-wide by tests that fail the build — every module taking a caller-supplied path must reach the filesystem sandbox helper, and every module taking a caller-supplied URL or host must reach an SSRF guard — so coverage is a CI property rather than a convention.

License

Apache License 2.0 — free for personal and commercial use.

Cloud Automation · Pricing · flyto2.com

Hosted deployment

A hosted deployment is available on Frontier AI.

_{Also known as: open source AI agent framework for production workflows · Python AI workflow automation with Playwright · MCP server automation with trace and replay · browser automation that can resume from a failed step}