StremAI
Shared memory layer for AI coding agents to store and recall learned information across sessions and tools.
README
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.
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.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.