Samvid Memory Studio
Samvid Memory Studio equips AI agents with enduring shared memory across interactions.
Open SourceProductivity
Visit website Free to browse · updated 2026-06-26
What is Samvid Memory Studio?
Samvid Memory Studio addresses the challenge of AI systems losing context between sessions by offering a unified memory layer that integrates with various interfaces and models. It organizes information into distinct categories such as facts, preferences, goals, and events while building connections that reflect support, contradiction, or causation between entries. The system incorporates mechanisms for memory evolution including importance-based retention and gradual decay for less relevant items. Additional capabilities allow for consolidation of similar entries, summarization of accumulated data, and replay of conversation sequences to restore full context without manual intervention. Lifecycle operations enable efficient maintenance through deletion of low-value items, space reclamation, and batch processing. This setup ensures the memory store remains functional and relevant as usage expands across different projects and tools.
Key features
Local-first persistent vector memory with 1024-dim embeddings
Knowledge graph with typed associations (supports, contradicts, supersedes, caused_by, implies)
16 memory types including fact, preference, rule, goal, plan, event
Importance-weighted decay with TTL and protected memories (≥0.9)
Lifecycle tools: forget, compact, consolidate, summarize
Episodic session recording and replay
MCP server for shared memory across AI agents and IDEs
What you can use Samvid Memory Studio for
Persistent Cross-Session Context
Retain full conversation history and decisions across restarts so AI agents recall prior choices like database selections without manual reminders.
Multi-Agent Shared Memory
Enable Claude, Cursor, VS Code, and other tools to access one unified memory store through the MCP server for consistent reasoning.
Typed Knowledge Graph Building
Automatically link memories with relations such as supports, contradicts, supersedes, caused_by, and implies to improve agent decision quality.
How to use Samvid Memory Studio
- 1Download the desktop app from the official site
- 2Install and launch Samvid Memory Studio
- 3Create namespaces for projects or topics
- 4Connect AI tools via the MCP server
- 5Begin session recording to populate memories
Samvid Memory Studio pricing
Pricing model: Open Source. Plan details are indicative — check the site for current prices.
V1.0
Free
- MIT LICENSED
- LOCAL-FIRST
- Download for free
Editor's verdict
Pros
- +Shared memory across multiple tools (Claude, Cursor, VS Code, Codex)
- +MIT licensed, local-first, free download
- +Automatic context loading without session reminders
Cons
- –Requires local installation and setup
- –v1.0 release with limited proven scale
- –No cloud synchronization mentioned
Our take: Samvid Memory Studio is a solid productivity choice. It's valued for shared memory across multiple tools (claude, cursor, vs code, codex) and mit licensed, local-first, free download. The main trade-off is requires local installation and setup. A good pick if you want capable AI without a high upfront cost.
Frequently asked questions
Yes, it runs entirely on-device with SQLite storage and supports offline use under an MIT license.
Summary
Samvid Memory Studio is a solid productivity choice. It's valued for shared memory across multiple tools (claude, cursor, vs code, codex) and mit licensed, local-first, free download. The main trade-off is requires local installation and setup. A good pick if you want capable AI without a high upfront cost.
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