Store facts, decisions, or context in encrypted persistent memory so they outlive the current session. Provide an existing cell ID to update that memory instead of adding new.
Apache 2.0
520,054 tools. Updated 2026-09-06 08:15
"Understanding Persistent Memory and Context Management" matching MCP tools:
- Save key-value pairs to persistent memory across sessions for remembering user preferences, installed skills, or project context.MIT
- Search persistent memory across SQLite and markdown files to retrieve prior context, feedback, project state, and session notes. Use at conversation start to recall relevant facts.MIT
- Save facts, documents, code, or user details into persistent memory for cross-session retrieval. Use for additive, non-destructive storage without context loss.Apache 2.0
- Store observations as persistent memories with optional tags, importance levels, context, and auto-expiration to manage AI agent memory.MIT
- Save facts, observations, or context to persistent memory for recall across sessions. Optionally categorize entries for organized retrieval.MIT
Matching MCP Servers
- AlicenseNot gradedqualityCmaintenanceA self-hostable MCP server that provides permanent memory for AI agents using Postgres + pgvector for semantic search and Markdown file sync.MIT
- AlicenseNot gradedqualityDmaintenanceA lightweight memory layer for MCP servers that persists user context across LLM sessions with minimal token cost, supporting key-value dedup, multi-tenant namespaces, and optional TTL.MIT
Matching MCP Connectors
- memoryOAuth
Persistent long-term memory for AI agents: semantic search, knowledge graph, and task canvas.
Persistent semantic memory for AI agents: store and recall text by meaning (RAG). x402
- Retrieve a stored value from persistent encrypted memory by key, enabling agents to recall prior context or credentials on demand.MIT
- Store a structured end-of-session summary in persistent memory so decisions, fixes, and discoveries made during AI coding sessions remain available for future context.MIT
- Save a memory entry to a persistent store for secure retrieval. Keep information organized with tags and optional agent isolation to ensure context-aware recall.Apache 2.0
- Access the complete Astria operating guide to learn available tools, recommended workflows, and best practices for persistent memory management.MIT
- Search persistent memory by semantic similarity to retrieve ranked, relevant past context for informed decisions.AGPL 3.0
- Store a dialog turn with role, content, and metadata to persistent session memory for later retrieval and context assembly.MIT
- List memory stores with summaries to identify the agent's persistent memory, attach it at session start to preserve history and context. Paginate via next_page.MIT
- Check the persistent memory vault status: enabled/disabled, note count, tag count, and disk path. Get insights into memory usage for cross-session context.MIT
- Delete all session memory data from the knowledge graph, including nodes, transcripts, and connections. Confirm to permanently clear the session's persistent context.Apache 2.0
- Search persistent memory before responding to project-specific questions to retrieve prior decisions and relevant context, ensuring answers align with saved work.MIT
- Fetch the complete agent context JSON from a finished analysis, containing file index, dependency graph, architecture layers, call chains, and database schema, for saving codebase understanding.MIT
- Store typed events in an agent's persistent memory log. Each appended event is retrievable later for context and reasoning.MIT
- Store facts, decisions, or context to encrypted persistent memory so agents retain information across sessions.Apache 2.0
- Store important notes, decisions, and preferences in persistent memory for access across sessions. This tool helps maintain project context and user patterns by saving searchable information to local storage.MIT
- Retrieve all stored memory keys from persistent storage to review saved data.MIT