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Adds a local, searchable persistent memory store for MCP agents.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.davidmosiah/delx-memory" MCP server from askskill: Run: claude mcp add 'io-github-davidmosiah-delx-memory' -- npx -y delx-memory
Please save these preferences to persistent memory for later retrieval: this project uses TypeScript by default, prefers a functional style, and should output in Chinese first.
Stores the preferences in searchable memory for later quick retrieval.
Please store this temporary note with a 24-hour TTL: the test environment URL is staging.example.com.
Stores a TTL-bound memory entry that expires automatically.
Please retrieve prior memories related to the keyword "release process" and summarize them as bullet points.
Returns matching memories and summarizes them into concise bullets.
Developers or AI agents can use it to retain project preferences, conventions, and recurring facts across sessions. It turns scattered context into searchable local memory.
When information is only useful for a short time, such as temporary URLs, one-off reminders, or short-lived task status, TTL helps keep stale entries out of the way.
When you need retrievable information that still requires care, its secret-safe local memory approach is suitable for sensitive config or restricted context.
It is a local-first persistent memory MCP tool built on a shared SQLite key/value store, with search, TTL, and secret-safe memory support.
From the provided information, it is an MCP tool, so you need an MCP-compatible client to connect to it. For more setup details, see the source repository.
It provides persistent, searchable, TTL-aware local memory instead of relying only on the current session. Compared with ephemeral context, it is better for reusable long-term information.
Store, search, and manage durable project facts, decisions, and conventions.
Give AI coding assistants persistent, structured project memory stored as local Markdown.
Provide persistent local semantic memory for MCP tools to store and search notes.
Give MCP clients durable memory for recalling user and project context.
Persist conversational memory with SQLite and retrieve context using metadata.
Give AI agents persistent memory and semantic retrieval across conversations.