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Shared memory bridge for AI agents to store and retrieve notes
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Claw Memory Bridge" yet — see the docs or source repo.
Save the decisions, rationale, and follow-up tasks from this refactor into shared memory so other AI agents can retrieve them later.
The tool stores the decision details in shared memory for later search and reuse.
Search shared memory for past notes, conclusions, and decisions related to “database migration strategy,” then return a summary.
Returns matching past records and key points to quickly restore context.
Write the key findings from this requirements research into shared memory so QClaw, Claude Code, and Codex can read them later.
The research notes are stored in the memory bridge for reuse by multiple agents.
Developers can store key decisions, conclusions, and context in shared memory while working with different coding agents, avoiding repeated background explanations. Later agents can retrieve that context and continue the work.
Researchers or product managers can save notes and conclusions over time, then search historical records by topic in later tasks to quickly restore context. This reduces information being scattered across separate conversations.
When a team prefers to keep shared AI agent memory locally first, it can use the SQLite-based storage option; TencentDB integration is also available optionally. This supports flexible storage choices.
It is a shared memory bridge for AI agents that supports storing, searching, and retrieving notes, decisions, and conclusions through MCP tools. The description says it can share context across QClaw, Claude Code, and Codex.
According to the description, it uses local SQLite by default and optionally integrates with TencentDB. See the source repository for exact configuration details.
The known prerequisite is that it is used within an MCP tool environment; if you want TencentDB support, you will also need the relevant database configuration. For exact installation steps and runtime requirements, see the source repository.
Give on-device AI agents persistent memory and hybrid context retrieval.
Store and retrieve persistent AI memories across sessions with contextual search.
Share, search, and reuse local memory across multiple AI coding agents.
Share project memory files over MCP across Claude Code and Claude.ai.
Store durable memory in a GitHub-hosted Obsidian vault via markdown tools.
Give MCP-compatible AI tools four-layer long-term memory for persistent context.