# FlyMy.AI - Infrastructure for AI-built software > Connect one FlyMy.AI MCP in your coding agent. Build with models, tools, memory and serverless execution, then run your workflow in the cloud by API or schedule. Page: https://flymy.ai/ Models / Tools / Serverless agents / One MCP # Vibe code an agent. Run it serverless. One MCP for all the models, tools and compute your agents need. Frozen runs make repeat jobs cheap and fast. [Start for free](https://app.flymy.ai/signup) [Connect FlyMy.AI](https://flymy.ai/#skill) Free to sign up. No seats, no minimum - you pay only when your agents run. claude flymyai build me an agent that answers our support emails One line. Any agent. 30 seconds. skill.md Connect using https://flymy.ai/skill.md + 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](https://flymy.ai/#install) **agents ready** trusted by 10,000+ agent builders 200,000+ agents running Trusted by teams and engineers at 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 - Claude - Codex - Cursor - Windsurf - Gemini - Copilot - Hermes - OpenClaw - + any MCP client ![FlyMy.AI](https://flymy.ai/assets/brand/flymyai-wing-wordmark.svg?v=866c7cb000f4) 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 agent → Run in the cloud → Call 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 with roles - run-only for sales, edit for engineers - or a connected account by email for a set number of days. 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-workflow example **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. Hand your agent the guide and it wires itself. Or set up MCP, the API or an embedded deployment by hand - same cloud behind all of them. 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 →](https://github.com/FlyMyAI/build-with-flymyai) ## The code is already written. The winners will be the teams that run it. Program your first agent in plain text - get back a versioned endpoint. [Spin up agents for free →](https://app.flymy.ai/signup) [Watch the live demos](https://flymy.ai/media/) --- For agents: the FlyMyAI operating guide (sign up, connect, run models, tools and agents) is https://flymy.ai/skill.md, and https://flymy.ai/llms.txt lists the other pages and the documentation.