flyto-core

The open-source execution engine for AI agents. 300+ atomic modules, MCP-native, secure by default.

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Flyto-core is a powerful Python library for geospatial analysis and visualization. It provides a wide range of tools for working with geographic data, including support for various file formats, spatial operations, and interactive mapping. With Flyto-core, users can easily load, manipulate, and visualize spatial data to gain insights and make informed decisions. Whether you are a GIS professional, a data scientist, or a developer, Flyto-core offers a versatile and user-friendly solution for geospatial tasks.

README:

Flyto2 Core

Deterministic execution engine for AI agents. 412 modules across 78 categories, MCP-native, evidence snapshots, execution trace, replay from any step.

Quick Start — Use with Your AI (MCP)

pip install flyto-core

Add to your MCP client config:

Claude Code

Run:

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

Or add to ~/.claude/settings.json:

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

Cursor

Add to .cursor/mcp.json:

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

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

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

Remote MCP Server (HTTP)

Run the server:

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

Then point any MCP client to the HTTP endpoint:

{
  "mcpServers": {
    "flyto-core": {
      "url": "http://localhost:8333/mcp"
    }
  }
}

Supports MCP Streamable HTTP transport — works with Cursor, Windsurf, and any standard MCP client that connects over HTTP.

Done. Your AI now has 412 tools — browser automation, Docker, file I/O, data parsing, crypto, scheduling, APIs, and more.

Claude ──┐
Cursor ──┤                    ┌─ browser.launch, .click, .extract (38 tools)
Windsurf ┼── MCP Protocol ──→ ├─ file.read, .write, .copy (8 tools)
Any AI ──┘                    ├─ data.csv.read, .json.parse, .xml.parse, .yaml.parse
                              └─ ... 412 modules across 78 categories

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

Quick Start — HTTP API

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

curl -X POST localhost:8333/v1/workflow/run \
  -H 'Content-Type: application/json' \
  -d '{
    "workflow": {
      "name": "example",
      "steps": [
        {"id": "step1", "module": "string.uppercase", "params": {"text": "hello"}},
        {"id": "step2", "module": "string.reverse", "params": {"text": "world"}}
      ]
    },
    "enable_evidence": true,
    "enable_trace": true
  }'

Endpoint	Purpose
`POST /mcp`	MCP Streamable HTTP transport (remote MCP server)
`POST /v1/workflow/run`	Execute workflow with evidence + trace
`GET /v1/workflow/{id}/evidence`	Get step-by-step state snapshots
`POST /v1/workflow/{id}/replay/{step}`	Replay from any step
`POST /v1/execute`	Execute a single module
`GET /v1/modules`	Discover all modules

Quick Start — Interactive Demo

pip install flyto-core[api]
python -m core.quickstart

Runs a 5-step data pipeline (file → JSON parse → template → format → export), shows the execution trace, evidence snapshots, and replays from step 3 — all in 30 seconds.

Why Flyto2 Core?

AI agents are running multi-step tasks — browsing, calling APIs, moving data. But after they finish, all you have is a chat log.

Flyto2 Core gives you:

412 Modules — composable building blocks across 78 categories (full catalog)
Execution Trace — structured record of every step: input, output, timing, status
Evidence Snapshots — full context_before and context_after at every step boundary
Replay — re-execute from any step with the original (or modified) context
Triggers — webhook (HMAC-verified) and cron scheduling for automated workflows
Execution Queue — priority-based queue with concurrency control
Workflow Versioning — semantic versioning, diff, and rollback
Usage Metering — built-in billing hooks for step/workflow tracking
Timeout Guard — configurable workflow and step-level timeout protection

Module Categories

Category	Count	Examples
`browser.*`	38	launch, goto, click, extract, screenshot, fill forms, wait
`flow.*`	24	switch, loop, branch, parallel, retry, circuit breaker, rate limit, debounce
`array.*`	15	filter, sort, map, reduce, unique, chunk, flatten
`string.*`	11	reverse, uppercase, split, replace, trim, slugify, template
`api.*`	11	OpenAI, Anthropic, Gemini, Notion, Slack, Telegram
`object.*`	10	keys, values, merge, pick, omit, get, set, flatten
`image.*`	9	resize, convert, crop, rotate, watermark, OCR, compress
`data.*`	8	json/xml/yaml/csv parse and generate
`file.*`	8	read, write, copy, move, delete, exists, edit, diff
`stats.*`	8	mean, median, percentile, correlation, standard deviation
`validate.*`	7	email, url, json, phone, credit card
`docker.*`	6	run, ps, logs, stop, build, inspect
`archive.*`	6	zip create/extract, tar create/extract, gzip, gunzip
`math.*`	6	calculate, round, ceil, floor, power, abs
`k8s.*`	5	get_pods, apply, logs, scale, describe
`crypto.*`	4	AES encrypt/decrypt, JWT create/verify
`network.*`	4	ping, traceroute, whois, port scan
`pdf.*`	4	parse, extract text, merge, compress
`aws.s3.*`	4	upload, download, list, delete
`google.*`	4	Gmail send/search, Calendar create/list events
`cache.*`	4	get, set, delete, clear (memory + Redis)
`ai.*`	3	vision analyze, structured extraction, text embeddings
`env.*`	3	get, set, load .env file
`git.*`	3	clone, commit, diff
`markdown.*`	3	to HTML, parse frontmatter, table of contents
`queue.*`	3	enqueue, dequeue, size (memory + Redis)
`sandbox.*`	3	execute Python, Shell, JavaScript
`scheduler.*`	3	cron parse, interval, delay
`ssh.*`	3	remote exec, SFTP upload, SFTP download
`graphql.*`	2	query, mutation
`dns.*`	1	DNS lookup (A, AAAA, MX, CNAME, TXT, NS)
`monitor.*`	1	HTTP health check with SSL cert verification

412 modules across 78 categories. See Full Tool Catalog for every module with parameters and descriptions.

Engine Features

Beyond atomic modules, flyto-core provides production-grade engine infrastructure:

Feature	Tier	Description
Execution Trace	Free	Structured record of every step: input, output, timing, status
Evidence Snapshots	Free	Full context_before and context_after at every step boundary
Replay	Free	Re-execute from any step with original or modified context
Breakpoints	Free	Pause execution at any step, inspect state, resume
Data Lineage	Free	Track data flow across steps, build dependency graphs
Timeout Guard	Free	Configurable workflow/step-level timeout protection
Webhook Triggers	Pro	HMAC-SHA256 verified webhooks with payload mapping
Cron Triggers	Pro	5-field cron scheduling with async scheduler loop
Execution Queue	Pro	Priority-based queue (LOW→CRITICAL) with concurrency control
Workflow Versioning	Pro	Semantic versioning, diff between versions, rollback
Usage Metering	Pro	Built-in billing hooks for step/workflow/module tracking

YAML Workflows

name: Hello World
steps:
  - id: reverse
    module: string.reverse
    params:
      text: "Hello Flyto"

  - id: shout
    module: string.uppercase
    params:
      text: "${reverse.result}"

flyto run workflow.yaml
# Output: "OTYLF OLLEH"

Python API

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())

Replay from a Failed Step

# Step 3 failed? Replay from there.
curl -X POST localhost:8333/v1/workflow/{execution_id}/replay/step3 \
  -H 'Content-Type: application/json' \
  -d '{}'

The engine loads the context snapshot at step 3 and re-executes from that point. No wasted computation.

Installation

# Core engine (includes MCP server)
pip install flyto-core

# With HTTP API server
pip install flyto-core[api]

# With browser automation
pip install flyto-core[browser]
playwright install chromium

# Everything
pip install flyto-core[all]

For Module Authors

from core.modules.registry import register_module
from core.modules.schema import compose, presets

@register_module(
    module_id='string.reverse',
    version='1.0.0',
    category='string',
    label='Reverse String',
    description='Reverse the characters in a string',
    params_schema=compose(
        presets.INPUT_TEXT(required=True),
    ),
    output_schema={
        'result': {'type': 'string', 'description': 'Reversed string'}
    },
)
async def string_reverse(context):
    params = context['params']
    text = str(params['text'])
    return {
        'ok': True,
        'data': {'result': text[::-1], 'original': params['text']}
    }

See Module Specification for the complete guide.

Project Structure

flyto-core/
├── src/core/
│   ├── api/              # HTTP Execution API + MCP HTTP transport (FastAPI)
│   ├── mcp_handler.py    # Shared MCP logic (tools, dispatch)
│   ├── mcp_server.py     # MCP STDIO transport (Claude Code, local)
│   ├── modules/
│   │   ├── atomic/       # 412 atomic modules
│   │   ├── composite/    # High-level composite modules
│   │   ├── patterns/     # Advanced resilience patterns
│   │   └── third_party/  # External integrations
│   └── engine/
│       ├── workflow/     # Workflow execution engine
│       ├── evidence/     # Evidence collection & storage
│       └── replay/       # Replay manager
├── workflows/            # Example workflows
└── docs/                 # Documentation

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Security

Report security vulnerabilities via [email protected]. See SECURITY.md for our security policy.

License

Source Available License — Free for non-commercial use.

Use Case	License Required
Personal projects	Free
Education & research	Free
Internal business tools	Free
Commercial products/services	Commercial License

See LICENSE for complete terms. For commercial licensing: [email protected]

Deterministic execution engine for AI agents.
Evidence. Trace. Replay.

For Tasks:

Click tags to check more tools for each tasks

analyze data visualize maps perform spatial queries create interactive plots geocode addresses

For Jobs:

gis analyst data scientist geospatial engineer urban planner environmental scientist

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