Streamient is an open-source shared memory layer for teams that need AI context across assistants, code review, support, stored email, and research. Browse every article below with its original image and content.
Streamient gives AI agents shared, searchable access to team decisions, links, emails, and Git history through MCP, so context carries across sessions and tools. The article invites readers to consider which workflow to delegate next.
We made Streamient retrieval broader, taught agents to verify prior decisions, and improved how they correct memory. It may use more tokens. Here’s why we think that tradeoff matters.
Evaluate a knowledge graph with real workflow questions, scoring both the assistant's response and the evidence it retrieves. Test time, permissions, and unanswerable cases, then track failures and rerun the same questions after changes.
Durable memory lets local LLM agents retrieve useful context after restarts without stuffing entire transcripts into prompts. The article explains how to store scoped, reviewable records, handle changing decisions, and test retrieval for relevance and accuracy.
AI agents break when context is scattered or stale. Streamient solves this with one editable, source-backed memory layer that validates facts and shares them across MCP-compatible tools like Claude, Cursor, and ChatGPT.
Long-horizon AI tasks fail when context gets crowded and goals drift. Streamient counters that with inspectable shared memory, compaction, offloading, todo-state, and retrieval so teams can keep durable facts across tools and sessions.
The article compares 10 Supermemory alternatives and argues that the key question is which memory layer can persist across tools and teams. It recommends Streamient for shared, inspectable context spanning notes, email, Git, and MCP-compatible AI clients.
AI agents need time-aware memory, not just retrieved facts. Temporal knowledge graphs preserve when facts were true, what replaced them, and their sources, helping agents avoid stale context and reason across changing workflows.
Search by exact tags, select records across pages, and move or retag them in bulk with familiar selection controls in Streamient.
You can now use the Streamient CLI to access your knowledge in your terminal, script, or agent workflow. We're also introducing new Obsidian two-way sync for even broader knowledge syncing.
MCP makes AI tools more useful. It does not magically give them memory. Here is the difference, and why builders need a real memory layer.
Here is a real-life use case for using an architecture like Kumbukum to not only save time but also a lot of tokens, i.e., money on your AI plans.