FlyMy.AI: Cloud That Can Think

Platform

MCP agents that
actually ship.

Use any MCP tool. One prompt, and the agent picks models, calls APIs, reasons through steps, and delivers the result. Same SDK, same infra, scales from a chatbot to a full pipeline.

Ship agents, not infrastructure

Describe what you need in a prompt. The agent picks models, calls tools, reasons through steps, and delivers the result. One run, and the whole cycle happens automatically.

Prompt → run Auto-routing Multi-model MCP tools

workflow.py

from flymy import AsyncFlyMy, FlyMyRunner client = AsyncFlyMy() runner = FlyMyRunner(client) response = await runner.run( input="Review PR #42, fix issues, deploy to prod", model=["claude-opus-4.6", "gpt-4o"], mcp_servers=["github", "vercel", "slack"], ) # Agent: review → fix 3 issues → deploy → notify #eng # 4 tools, 2 models, 12 steps, 38s total

Every tool your agent needs

Gmail, Slack, GitHub, HubSpot, Notion, Jira, every major MCP tool with managed OAuth out of the box. Describe the workflow in a prompt. The agent figures out which tools to call and when.

OAuth managed MCP tools Event triggers Custom tools

lead_scorer.py

from flymy import AsyncFlyMy, FlyMyRunner client = AsyncFlyMy() runner = FlyMyRunner(client) response = await runner.run( input="""For each new inbound lead: 1. Read email from Gmail 2. Enrich contact in HubSpot 3. Score and qualify 4. Notify sales team in Slack""", model="claude-sonnet-4.5", tools=["gmail", "hubspot", "slack"], auth="managed", ) # 47 leads → 12 qualified → Slack notified

Catches regressions before your team does

New PR opens, and the agent reads the diff, runs analysis, searches for related past issues, posts a structured review, and files a ticket if it finds something critical. Fully autonomous.

GitHub MCP Linear MCP Slack MCP Auto-triage

code_review.py

from flymy import AsyncFlyMy, FlyMyRunner client = AsyncFlyMy() runner = FlyMyRunner(client) response = await runner.run( input="""On every new PR in repo acme/backend: 1. Read the diff via GitHub 2. Analyze for bugs, security issues, style 3. Search past issues for related regressions 4. Post a structured review comment 5. If critical, file a Linear ticket, ping #eng""", model="claude-opus-4.6", mcp_servers=["github", "linear", "slack"], trigger="github.pull_request.opened", ) # 142 PRs reviewed, 23 bugs caught, 0 false positives

Resolves tickets before a human sees them

New ticket in Zendesk, and the agent classifies urgency, searches the knowledge base in Notion, drafts a resolution for routine issues, routes complex ones to the right team with full context.

Zendesk MCP Notion MCP Slack MCP Auto-resolve

support_triage.py

from flymy import AsyncFlyMy, FlyMyRunner client = AsyncFlyMy() runner = FlyMyRunner(client) response = await runner.run( input="""For each new Zendesk ticket: 1. Classify urgency and category 2. Search Notion knowledge base for solution 3. If routine, draft reply, send to customer 4. If complex, route to team in Slack with context 5. Update ticket status and tags""", model="claude-sonnet-4.6", mcp_servers=["zendesk", "notion", "slack"], trigger="zendesk.ticket.created", ) # 847 tickets/week, 62% auto-resolved, CSAT 4.7

Ships release notes while the code ships

PR merged to main, and the agent summarizes commits, checks deploy status, writes release notes to Notion, announces in Slack, sends a customer-facing digest via Gmail. Zero manual steps.

GitHub MCP Notion MCP Slack MCP Gmail MCP

release_ops.py

from flymy import AsyncFlyMy, FlyMyRunner client = AsyncFlyMy() runner = FlyMyRunner(client) response = await runner.run( input="""When PR merges to main: 1. Summarize all commits since last tag 2. Check deploy status on Vercel 3. Write release notes → Notion docs 4. Announce in #releases on Slack 5. Email digest to customers via Gmail""", model="claude-sonnet-4.6", mcp_servers=["github", "vercel", "notion", "slack", "gmail"], trigger="github.push.main", ) # v2.14.0 shipped → notes → Slack → 1.2k customers emailed

from flymy import AsyncFlyMy, FlyMyRunner

client = AsyncFlyMy()
runner = FlyMyRunner(client)

response = await runner.run(
  input="Ship a release and notify the team",
  model=["claude-opus-4.6", "gpt-4o"],
  mcp_servers=["github", "slack"],
  tools=['search_files', 'run_tests', 'deploy'],
)

# Agent reasons, selects tools, and acts
print(response.reasoning)  # full chain-of-thought
print(response.actions)    # tools used + results

Developer experience

Three lines to
a thinking agent.

No prompt engineering. No chain management. No tool wiring. Just describe what you need, and FlyMy.AI handles the reasoning.

TypeScript SDK with full type safety

Streaming responses with reasoning steps

Works with Claude Code, Cursor, and any IDE

Ecosystem

Everything you need,
unified.

Every model, every MCP tool, and growing. One API key to access the entire AI stack.

Claude Opus 4.6

Anthropic: frontier reasoning, analysis

GPT-5.2

OpenAI: next-gen multimodal, agents

Gemini 3 Pro

Google: long context, vision and video

Llama 4 Maverick

Meta: open-source, customizable

Mistral Large

Mistral: multilingual, efficient

DeepSeek R1

DeepSeek: reasoning, math, code

Nano Banana Pro

Google: image model for media agents

Claude Sonnet 4.5

Anthropic: fast, balanced, reliable

Veo 3.1

Google: SOTA video, audio & effects

Web Search

Real-time search across the web

Code Execution

Sandboxed Python, JS, shell runtime

File Operations

Read, write, parse any file format

Web Browser

Headless Chrome, screenshots, DOM

Database Query

SQL, NoSQL, vector DB access

API Calls

HTTP requests, webhooks, REST/GraphQL

Image Analysis

Vision, OCR, image generation

Email & Messaging

Send emails, Slack, Teams messages

Auth & Security

OAuth, JWT, secrets management

GitHub

Repos, PRs, issues, actions

Google Workspace

Drive, Docs, Sheets, Calendar

Slack

Channels, messages, workflows

HubSpot

CRM, contacts, deals, marketing

Notion

Pages, databases, knowledge base

Jira

Issues, sprints, project tracking

Salesforce

CRM, leads, opportunities, reports

Zapier

Workflow automation via Zapier MCP

Custom MCP

Build your own server in minutes

Any

Foundation models

Any

MCP tools

<100ms

Routing latency

The agentic cloud.

A new way to ship agents that thinks.

Teach it in text, not code.

Plug in tools, safely.

Ship it. Embed it.

Safe by default.

Encrypted key vault

Sandboxed runtime

Scoped tool access

MCP agents that
actually ship.

Ship agents, not infrastructure

Every tool your agent needs

Catches regressions before your team does

Resolves tickets before a human sees them

Ships release notes while the code ships

Infrastructure for agents
with reflexes.

Three lines to
a thinking agent.

Everything you need,
unified.

Watch it
reason.

From prompts to
production.

The agentic cloud.

A new way to ship agents that thinks.

Teach it in text, not code.

Plug in tools, safely.

Ship it. Embed it.

Safe by default.

Encrypted key vault

Sandboxed runtime

Scoped tool access

MCP agents thatactually ship.

Ship agents, not infrastructure

Every tool your agent needs

Catches regressions before your team does

Resolves tickets before a human sees them

Ships release notes while the code ships

Infrastructure for agentswith reflexes.

Three lines toa thinking agent.

Everything you need,unified.

Watch itreason.

From prompts toproduction.

MCP agents that
actually ship.

Infrastructure for agents
with reflexes.

Three lines to
a thinking agent.

Everything you need,
unified.

Watch it
reason.

From prompts to
production.