Working
This task
A short-lived scratchpad with TTL expiry. Agents keep the current job in view without stuffing the whole vault into context.
Storm Data is organic cloud memory any MCP-compatible agent can plug into. Storm MCP connects those agents to 1,100+ tools. One ecosystem for knowledge that lasts and actions that stay in your control.
Persistent, compartmentalized memory — plus a gateway that traces every tool call.
Most agents forget the moment a chat ends. Storm Data is the shared memory layer in between — persistent, compartmentalized, and one MCP paste away. What Claude learns today, Cursor can use tomorrow.
This task
A short-lived scratchpad with TTL expiry. Agents keep the current job in view without stuffing the whole vault into context.
What just happened
Timestamped summaries with recency decay. Yesterday’s decisions stay findable; last month’s noise fades on its own.
What is true
Deduplicated facts and preferences that persist. The durable layer every agent can query across sessions and tools.
Split memory by project, team, or personal context. Each vault has its own retention and access rules.
Generate an MCP URL with only the read/write permissions that agent should have. Revoke it any time.
Drop the endpoint into Claude, Cursor, ChatGPT, or any MCP-compatible agent. No custom backend to maintain.
Overnight, Storm Data distills raw notes into facts, finds relationships, and consolidates dormant compartments.
Storm Data keeps the context. Storm MCP lets agents act on it — securely, across any system. No token headaches, no brittle OAuth glue, no integrations that fall apart after one session.
Drop-in compatible with OpenAI, Anthropic, and LangChain.
from storm import Storm
from openai import OpenAI
# Initialize Storm with your tools
storm = Storm(
api_key="storm_...",
tools=["google-calendar", "slack", "stripe"]
)
client = OpenAI(base_url="https://api.storm.dev/v1")
# Models can now use tools securely
response = client.chat.completions.create(
model="gpt-4",
messages=[{
"role": "user",
"content": "Check my calendar and invoice the client if the work is done."
}],
tools=storm.tools,
)Memory, tools, routing, and notes — built to work together instead of trapping context in one app.
A unified gateway connecting AI clients to any service through MCP servers
Connect to all your favorite tools with one-click OAuth or API key authentication
Get in touch to talk through Storm Data memory, Storm MCP gateways, and custom integrations.
Storm Data memory, Storm MCP discovery, and Storm Router orchestration — already live
Persistent Cross-Agent Knowledge
Three-tier memory that grows with you—working, episodic, and semantic. What Claude learns today, Cursor remembers tomorrow. Compartmentalized and user-controlled.
Try Organic MemorySelf-Organizing Memory
Nightly batch processing that distills raw memories into durable facts, discovers relationships, deduplicates knowledge, and consolidates dormant compartments automatically.
Try Sleep CyclesDynamic Tool Discovery
Say goodbye to context rot. Radar intelligently searches and caches tools, delivering only what your AI needs—reducing token usage by 60-80%.
Try RadarPre-Built AI Configurations
One-click gateway templates tailored for specific roles—Crypto Trader, Data Scientist, DevOps Engineer, and more. Start productive instantly.
Try PersonasSmart Context Management
Optimize your token spend with intelligent context routing. Little Chef uses smaller models to manage context, only calling expensive models when needed.
Try Little ChefMulti-Agent Discussions
Orchestrate conversations between multiple AI models. Watch different perspectives debate, collaborate, and arrive at better solutions together.
Try Round TableExciting projects coming soon to expand the Storm ecosystem
Platform for Agent skills based on Anthropic's open-sourced standard
Bring Your Own Server—deploy and manage your own MCP infrastructure
Connect multiple instances of the same app simultaneously for power users
Red teaming and security testing for AI systems
Programmatic tool use that scales with your workflow