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The agent cloud you program in plain text.Infrastructure for AI-built software.

Vibe code it.
FlyMy.AI runs it.

Build thinking agents in plain text - in Claude, Codex or Cursor. One MCP hands them models, tools, memory and GPUs. When an agent works, leave it running in our cloud - by API or on a schedule.Build thinking agents in plain text - in Claude, Codex or Cursor. One MCP hands them models, tools, memory and GPUs. When an agent works, leave it running in our cloud - by API or on a schedule.

Connect FlyMy.AIConnect FlyMy.AI see it run live
claudeflymyai build me an agent that answers our support emails▋
One line. Any agent. 30 seconds.
skill.md Connect using https://flymy.ai/skill.md
HermesOpenClaw+ any agent

Paste it into the coding agent you already use. It wires up the models, tools, memory and cloud runtime for you. Or set up MCP by hand

agents ready
000 ready :: waiting for task
agents--
teams--
active--
handoffs00
done00
trusted by
10,000+
agent builders
200,000+
agents running
Artificial Analysis NVIDIA Google Stability AI
one MCP in - all of this behind it

Models and tools. One MCP.

Discover models and tools through one MCP. Use them together in a workflow that keeps its state and run history.
Platform map

One MCP.
Everything your workflow needs to run.

Stay in Claude, Codex or Cursor. Ask for a model, a tool, a scheduled run, a file from last time - it is all one endpoint, and it all lands in the same run with its state, files and history. Everything on this map is live today.

Level 1 · Infrastructure
ClaudeChatGPTCursorWindsurfGeminiCopilotHermesOpenClaw+ any MCP client
FlyMy.AI ONE MCP integrates in 30 seconds

Everything here is live today. Your workflow keeps its state, files and run history between runs.

Build in your coding agentRun in the cloudCall by API or schedule

// the blocks above, what they do together below

one connector in - here's what changes
Chat → agent → API
Test your workflow, save a version, and call it from your product. Inspect each cloud run.
>freeze this as an api
Local → cloud
Build and test the workflow in your coding agent. Leave it running in the cloud after the chat ends.
>take this chat to the cloud, keep it running
Parallel cloud runs
Run independent tasks in parallel with serverless agents. Inspect each run and its result.
>run this across all 3,000 rows in parallel
Cloud browsers
Use connected browser tools to fetch pages and automate web steps inside your workflow.
>send 200 agents to check every page
Runs on a schedule
Every morning, every hour, every Monday. Works nights, reports back before you wake.
>email my users their digest at 8
MCP
Tools in the same workflow
Discover available tools, connect the accounts you need, and call them alongside models.
>post the report to slack and notion
State and history stay together
Your FlyMy.AI workflow keeps its context, files and run history in the cloud. Continue working from your connected coding agent.
>continue this workflow from codex
Human in the loop
On money, sends, deletes - it stops and asks first. Approve in one tap, it goes on. Every run recorded.
>always ask before refunds over $500
Built for teams
Share an agent by link. Roles and permissions - run-only for sales, edit for engineers - one dashboard of every run.
>give the team run-only access
FlyRouter™ - models and tools

Every lane. One router.

Discover a model or tool, inspect its inputs, then use it inside the same workflow. FlyMy.AI keeps execution and run history together.

Product in action

Your working workflow.
A cloud API.

Save a workflow version and run it by API or schedule, with state and history attached. Versioning fixes the workflow definition; external model outputs can still vary.

// three public builds show the workflows and how to run them

Controls

Set the budget.
See every run.

Choose the model. Gate sensitive actions. Keep spend, calls and results in one run history.

run / video-workflowexample
model.choice
set by you
budget.limit
$0.50
run.cost
$0.27
credentials
vault
send.email
awaiting approval
run.trace
recorded
spend / limit$0.27 / $0.50

Model calls, tools, latency, cost and results - attached to the run.

Set the limit before you run.

Give the run a budget. Track its spend against the limit.

Switch to a cheaper model.

Choose a lower-cost model for the next run. Keep the workflow and its history.

Approve before it acts.

Put an approval gate before a send, payment or delete.

See what happened.

Inspect calls, latency, cost and results. Find the step that needs attention.

// connect your coding agent. keep control of what runs.

Ways in

Your coding agent already
knows how to use this.

Wire the endpoint yourself, or hand your assistant the guide and let it wire itself. Same cloud behind both.

Of 397 companies in YC's two newest batches, 116 - 29% - are building agents, models and tools.
Their AI workflows can run here today. methodology →

The code is already written.
The winners will be the teams that run it.

Program your first workflow in plain text - get back a versioned endpoint.

Start free → Watch the live demos