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Give AI assistants persistent memory with tagged retrieval, links, and source references.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-ltm" yet — see the docs or source repo.
Save the following project background to long-term memory: The project is called Apollo, and the goal is to launch an enterprise knowledge base Q&A feature in June. The stack is Next.js, FastAPI, and PostgreSQL. Key constraints: must support SSO and audit logs. Add tags: project, Apollo, tech-stack, constraints, and create a link to the topic 'enterprise knowledge base'.
The tool stores the project context as long-term memory with tags, topic links, and traceable sources for future sessions.
Retrieve records from long-term memory related to the Apollo project that include the tags 'SSO' or 'audit logs', then summarize the architecture decisions we made earlier, why we made them, and the related sources.
It returns matching memory entries and a source-backed summary of past decisions to quickly restore context.
Add this new information to long-term memory: 'The client wants the Q&A system to integrate with Confluence and Notion first, and Google Drive in phase two.' Link it to Apollo, data source integration, and roadmap, and mark the source as today's client meeting notes.
The tool creates a new memory entry with linked relationships and source attribution for topic-based navigation later.
Give AI agents persistent memory with semantic recall and maintenance tools.
Give MCP-compatible AI agents persistent local memory across sessions.
Provide persistent local semantic memory for MCP tools to store and search notes.
Give AI assistants persistent memory for preferences, context, and decisions.
Give AI agents persistent memory with semantic search and automatic linking.
Give AI assistants persistent memory, adaptive recall, and graph-based knowledge retrieval.