StremAI

io.github.thomasjumperPublished by GitHub account thomasjumperv1.2.5Updated Oct 24, 2026

StremAI MCP: shared memory for AI coding agents. Connected agents can recall. OAuth + local stdio.

VerifiedStreamable HTTPWeb executableKnowledge & MemoryDeveloper Tools

Overview

AI-generated overview

StremAI is a shared memory layer for AI coding agents, letting connected agents store what they learn and recall it later across sessions, machines and tools.

What you can do
  • Store learned context from coding work: architectural decisions, setup gotchas, repo-specific commands and pitfalls
  • Recall stored memories by topic so a new session or a different agent starts with prior context
  • Share handoffs and project facts between agents in Claude Code, Cursor, Codex and other MCP clients
  • Manage memory entries: human-readable, attributed to the storing agent, and exportable, archivable or erasable
When to use it
Useful when you keep re-explaining the same repo, conventions or decisions to each new agent session, when context is lost between sessions or machines, or when several coding tools should share what one of them learned.
Requirements
A StremAI account with OAuth browser sign-in against the hosted endpoint, or an API key sent as a Bearer Authorization header for clients that cannot do OAuth. A local fallback is available via the npm package aiagentsbay-mcp over stdio (Node.js) or the Python package stremai. Network access to the hosted service.
Before you install
Memories are stored on a third-party hosted service, so anything an agent records leaves your machine; avoid storing secrets or sensitive code details. An API key is a credential and should be kept out of shared configs. Entries can be exported, archived or erased, so agents may change or remove stored memory.

Installation

In SourceWeft

  1. Open StremAI in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.thomasjumper%2Fstremai/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "mcpServers": {
    "stremai": {
      "type": "http",
      "url": "https://stremai.com/api/mcp"
    }
  }
}

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.

[PyPI] [npm] [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

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.

Source: README.md at commit 643a3d9

Tools

0
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Version history

1
  1. v1.2.5LatestSep 16, 2026

Score

85% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts