StremAI
# 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.
[](https://pypi.org/project/stremai/) [](https://www.npmjs.com/package/@tmjumper/stremai) [](https://www.npmjs.com/package/aiagentsbay-mcp) [](LICENSE)
## 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/mcp` with 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 `agentbay` or `aiagentsbay-mcp` names so existing installs keep working.
## Connect Claude Code
```bash
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:
```json
{
"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:
```json
{
"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:
```bash
npx -y aiagentsbay-mcp@latest
```
The package name is legacy compatibility; new docs and server aliases use `stremai`.
Python:
```bash
pip install stremai
```
```python
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](https://stremai.com)
- MCP docs: [stremai.com/docs/mcp-memory](https://stremai.com/docs/mcp-memory)
- Claude Code memory: [stremai.com/docs/claude-code-memory](https://stremai.com/docs/claude-code-memory)
- Python SDK: [stremai.com/docs/python-sdk](https://stremai.com/docs/python-sdk)
- AI answer inventory: [stremai.com/llms-full.txt](https://stremai.com/llms-full.txt)
## Install guides
- [Claude Code](docs/install/claude-code.md)
- [OpenAI Codex CLI](docs/install/codex-cli.md)
- [Cursor](docs/install/cursor.md)
- [OpenClaw](docs/install/openclaw.md)
- [Hermes](docs/install/hermes.md)
## Comparison reads
- [vs. GBrain](docs/vs/gbrain.md)
- [vs. Mem0](docs/vs/mem0.md)
- [vs. Letta](docs/vs/letta.md)
- [vs. Zep](docs/vs/zep.md)
## 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](LICENSE) for everything in this repository.
TDQS
Scored across 9 tools
Each tool targets a distinctly different action: storing, recalling, forgetting, verifying, inspecting health, compacting, signing up, capabilities introspection, and auth status. There is no meaningful overlap or ambiguity between them.
Most tools follow a clear agentbay_memory_<action> pattern, while signup, capabilities, and whoami diverge slightly by dropping the memory_ segment. The naming is still predictable and readable, but not perfectly uniform.
Nine tools is well-scoped for a memory-management server. Each tool maps to a real user need without redundancy or bloat.
The core memory lifecycle is covered: store, recall, forget, verify, health, and compact. A minor gap is the lack of an explicit update/edit operation for existing memory content, though verify partially addresses freshness.