StremAI
Allows agents in OpenAI Codex CLI to store and recall memory via StremAI's shared memory layer.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@StremAIstore that the CI pipeline uses GitHub Actions with Node 18"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
StremAI
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.
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.
Related MCP server: mindkeg-mcp
Connect Claude Code
claude mcp add --transport http stremai https://stremai.com/api/mcp --scope userThen 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@latestThe package name is legacy compatibility; new docs and server aliases use stremai.
Python:
pip install stremaifrom 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.
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