StremAI

Use the local stdio package or API-key fallback for CI, scripts, and MCP clients that cannot complete OAuth.

After connecting, run this verification prompt: > Use StremAI project memory and test store/recall. > store a test memory titled "setup check" with content "StremAI is wired up" using projectId > recall the test memory you just stored using projectId > tell me which recall strategies found it

Then ask it to recall the test memory in a fresh session or second connected client. A working MCP memory connection should return the setup check rather than asking you to repeat it.

Skip it if you use one AI tool, in one repository, on one machine, and its built-in memory plus a CLAUDE.md or AGENTS.md file covers you; you work solo and are happy hand-curating notes into instruction files; or you want fully local, self-managed infrastructure. Open-source MCP memory servers are a reasonable choice if you prefer running your own. StremAI earns its place when agents span multiple tools, machines, or teammates, and when you want memory that is shared, attributed, and user-controlled without operating the layer yourself.

StremAI is an MCP server. Any MCP-compatible client can connect to it — hosted over HTTP at stremai.com/api/mcp with OAuth sign-in, or via a local stdio package — and gains memory tools: store, recall, verify, and session handoff. When an agent calls recall, StremAI searches stored memories several ways at once: aliases, tags, keywords, semantic similarity, and returns a small ranked set of relevant entries rather than a full dump. Because MCP is an open standard, one memory layer can serve several different tools. Verified with Claude Code and Claude Desktop; other MCP clients are supported or in active verification.

Can multiple tools share one memory layer?

Yes. Because MCP is an open standard, one StremAI memory layer can serve several compatible tools connected to the same account or project.

No. Stored memories are used to serve your own recalls — nothing else. StremAI stores the short entries agents explicitly save, not your codebase; there is no repository ingestion or ambient capture. Memory content is encrypted in transit and at the field level at rest, and search embeddings are generated via a subprocessor named in the privacy policy solely so your own recall works. There is no cross-customer access, and no model training on user data. If model-adaptation features are ever offered, they would be opt-in and permissioned — today they do not exist. Details: stremai.com/security.

OAuth/browser sign-in is preferred. API keys stay available for CI, scripts, and clients that cannot complete OAuth.

Persistent memory for AI assistants and coding agents across ChatGPT, Claude, Cursor, and other MCP-compatible tools.

Shared memory layer for AI coding agents with dream pipeline distillation, session grounding, and multi-instance coherence.

OpenMemBrain is the intelligent membrane for AI coding memory. It autonomously reads and learns from your coding sessions — you never have to tell it what to save. It selectively absorbs project knowledge, blocks secrets, filters noise, resolves conflicts, and persists only what matters.

Shared memory for coding agents. Stop re-explaining your codebase every session. Hosted MCP at https://teamshared.com/mcp with email/OTP Connect.

Provides perfect memory for AI-assisted development by capturing project context snapshots, enabling natural language search, evolution tracking, and code intelligence.

Persistent memory and semantic search for AI coding assistants across sessions

Local Work Model for AI agents that learns from real outcomes.

Auditable, self-improving knowledge & memory for AI agents over MCP — citation-enforced answers and a replayable why-trace, self-hosted on Postgres.

Local stdio MCP server for coding agents: shared troubleshooting memory, agent-to-agent help posts, replies, and a unified inbox. Quick start: npx -y agent-only-mcp