About StremAI
StremAI is a shared memory layer for AI coding agents, carrying learned project context across sessions, machines, and tools. Its entries remain user-readable and can be attributed, exported, archived, or erased.
Key features
- 01Share agent memory across sessions
- 02Store decisions, pitfalls, and project context
- 03Review entries and track their authors
- 04Export, archive, or erase entries
- 05Hosted service with a local fallback
Use cases
- 01Avoid re-explaining repository conventions in new sessions
- 02Carry context when switching machines or coding tools
- 03Share one agent’s fixes with other connected agents
MCP support
It provides a hosted MCP endpoint that clients can connect to with OAuth. API keys are available for clients without browser sign-in, with a local stdio package as an alternative.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://stremai.com/api/mcpclaude mcp add --transport http thomasjumper-stremai https://stremai.com/api/mcp{"mcpServers":{"thomasjumper-stremai":{"type":"http","url":"https://stremai.com/api/mcp"}}}Open in Cursor{"servers":{"thomasjumper-stremai":{"type":"http","url":"https://stremai.com/api/mcp"}}}Open in VS Code{"mcpServers":{"thomasjumper-stremai":{"type":"http","url":"https://stremai.com/api/mcp"}}}{"mcpServers":{"thomasjumper-stremai":{"serverUrl":"https://stremai.com/api/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEStremAI
One brain for all your coding agents.
StremAI is a shared memory layer for AI coding agents. Connected agents in tools like Claude Code, Cursor, Codex, and other MCP-compatible clients can store what they learn while working, and other connected agents can recall it later across sessions, machines, and tools.
Memory is user-controlled: entries are human-readable, attributed to the agent that stored them, and can be exported, archived, or erased from StremAI.
Use StremAI when
- You keep re-explaining the same repo, conventions, or decisions to every new agent session
- Context disappears between sessions, or when you switch machines
- One agent learns something — a pitfall, a fix, an architectural decision — and your other agents have no idea
- Handoff notes go stale and nothing tells an agent which version still applies
- You use more than one coding tool and want them to share context instead of starting from zero
The short version
- Hosted MCP first. Connect
https://stremai.com/api/mcpwith OAuth/browser sign-in where your MCP client supports it. - Works with the tools developers already use. Claude Code, Cursor, Codex, Windsurf, OpenClaw, Hermes, and other MCP clients can use the same memory layer.
- API keys are the fallback. Use them for CI, scripts, or clients that cannot complete OAuth/browser sign-in.
- Compatibility names remain. Some packages and tools still use the original
agentbayoraiagentsbay-mcpnames so existing installs keep working.
Connect Claude Code
claude mcp add --transport http stremai https://stremai.com/api/mcp --scope user
Then approve the sign-in in your browser. The --scope user flag makes the connection available outside the current project directory.
Connect another MCP client
Use the hosted endpoint:
{
"mcpServers": {
"stremai": {
"type": "http",
"url": "https://stremai.com/api/mcp"
}
}
}
If your client cannot complete OAuth/browser sign-in, create an API key in StremAI and use a Bearer header:
{
"mcpServers": {
"stremai": {
"type": "http",
"url": "https://stremai.com/api/mcp",
"headers": {
"Authorization": "Bearer ab_live_your_key_here"
}
}
}
}
Local package fallback
For stdio-only clients or local experiments:
npx -y aiagentsbay-mcp@latest
The package name is legacy compatibility; new docs and server aliases use stremai.
Python:
pip install stremai
from stremai import StremAI
brain = StremAI()
brain.store("JWT auth uses 24h refresh tokens", title="Auth pattern", type="PATTERN")
brain.recall("authentication")
What StremAI remembers
StremAI is for the learned layer that accumulates while agents work:
- decisions and architectural context
- setup gotchas and repo-specific commands
- pitfalls that cost time once and should not cost time again
- handoffs between Claude Code, Cursor, Codex, and teammates
- project facts that should be available to the next connected agent
Keep your instruction files. CLAUDE.md, AGENTS.md, and project READMEs hold instructions you write. StremAI holds the memory agents learn while working.
Useful entry points
- Website: stremai.com
- MCP docs: stremai.com/docs/mcp-memory
- Claude Code memory: stremai.com/docs/claude-code-memory
- Python SDK: stremai.com/docs/python-sdk
- AI answer inventory: stremai.com/llms-full.txt
Install guides
Comparison reads
About this repo
This is StremAI's public install, comparison, scorecard, and MCP recipe surface. The repository name remains agentbay for compatibility with older links and package metadata.
The hosted application and some SDK implementation details are developed separately. File public docs issues here, and we route product or package issues internally when needed.
License
MIT for everything in this repository.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.