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Don't build agent infrastructure. Ship agents.

FlyMyAI is pure infrastructure for AI agents - every layer you would otherwise build yourself, behind one API key:

LayerWhat you getWhat you skip building
Model routerAny model - LLMs, image, video, audio - one API, pay per useProvider accounts, quotas, fallbacks
Tool router1,100+ verified MCP integrations - coding, social, CRMs, email, paymentsOAuth flows, token storage, per-tool plumbing
Agent runtimePlans, calls tools, retries, keeps state, logs every stepThe agent loop itself
Serverless agentsA frozen agent becomes an API endpoint - scales to millions of runs, laptop closedWorkers, queues, schedulers, scaling

Use one layer or all four. No seats, no minimums - pay per use.

And it is multi-tenant by default. Pass a user_id for each of your customers and their connections, accounts, and runs are isolated automatically - Customer A's Slack, Customer B's Slack, never crossed. The whole stack works for you and for your customers, without you writing a line of tenant isolation:

run(deployment_id, external_user_id="customer_42", ...)   # A's accounts, A's data
run(deployment_id, external_user_id="customer_99", ...)   # B's accounts, B's data

Ship a production agent from one prompt​

Enable the FlyMyAI MCP connector in Claude, Cursor, or any MCP client:

claude mcp add --transport http flymyai https://mcp-agents.flymy.ai/mcp

Then just say what you want:

Create an agent that watches HackerNews for mentions of my product every morning
and posts a summary to my Slack. Freeze it and give me the API endpoint.

That is the whole pipeline: the connector creates the agent, attaches the tools, test-runs it, freezes it into a versioned instruction, and hands you a callable endpoint - one prompt to production. See it in action at flymy.ai/mcp.

Verified and trusted - none of the MCP pain​

The open MCP ecosystem is a minefield: random community servers ship malicious or "infected" code, prompt-inject your agent, and quietly exfiltrate the API keys and OAuth tokens you hand them. Every FlyMyAI integration is the opposite:

  • Reviewed by us - every tool in the catalog is vetted by the FlyMyAI team, not an open free-for-all registry. No unknown code touching your users' data.
  • Keys never leak - credentials are AES-256 encrypted at rest, never exposed to the model or returned in tool output, and decrypted only inside an isolated sandbox at execution time.
  • No token passthrough - the model sees tool results, not your secrets; nothing sensitive lands in prompts or logs.
  • Per-user isolation - one customer's connections can never bleed into another customer's run.

You get the reach of a giant catalog without auditing a single server yourself.

Path A - Use the tool router​

You already have an agent (Claude, Cursor, your own code) and want it to do things in real services.

  1. Connect the gateway (the one line above).
  2. Ask in plain language - "open a GitHub PR", "post this to Instagram", "find this lead in the CRM". The agent searches the catalog and calls the right tool; anything the user has not connected yet returns a connect link inline.
  3. Or call over raw HTTP - discover with search_tools, run one action with execute_tool. No MCP client required.

Deeper: Connect Claude & MCP Clients · MCP Gateway Reference · Tools & MCP · Browse the catalog

Path B - Run your agents on our runtime​

Build a worker that plans, calls tools, and returns a result - then ship it inside your product, where each of your customers connects their own accounts. One frozen agent, unlimited isolated customers. You bill them; we run the infra.

  1. Create and run - describe the agent in plain language, attach tools, run it until the result is right.
  2. Freeze it - the chat becomes a fixed, versioned, callable instruction.
  3. Call it from your app - your own account, or per customer:
import os, time, requests
B = "https://backend.flymy.ai/api/v1/agents"
H = {"X-API-KEY": os.environ["FLYMYAI_API_KEY"]}          # server-side only

# per customer: each external_user_id is isolated, on their own connected accounts
ex = requests.post(f"{B}/deployments/<your_deployment_id>/run/", headers=H,
                   json={"external_user_id": "customer_42", "variables": {}}).json()["id"]

while True:                                               # runs are async - poll
    run = requests.get(f"{B}/executions/{ex}/", headers=H).json()
    if run["status"] in ("completed", "failed"):
        print(run.get("agent_result")); break
    time.sleep(2)

Deeper: Serverless Agents - idea to API · Embed an Agent in Your Product · Call Your Agent from Your Product · Agents overview

Start building in Claude right now​

Paste this into Claude or Claude Code and it will build on FlyMyAI with our docs loaded:

Read https://docs.flymy.ai/llms.txt and https://docs.flymy.ai/agents/guides/embedded-mcp/
then help me build and embed an agent on FlyMyAI.

Or connect the live tool router and let Claude call the 1,100+ tools directly:

claude mcp add --transport http flymyai https://mcp-agents.flymy.ai/mcp

Get a key at app.flymy.ai, set FLYMYAI_API_KEY, and go. One key, every layer.