Search long-term memory to retrieve past user preferences, project decisions, or earlier context. Returns relevant matches ranked by semantic similarity.
MIT
306,580 tools. Last updated 2026-07-27 02:50
"Understanding Cursor or Cline Context in Long-term Memory Systems" matching MCP tools:
- Guards Xcode agent sessions against context compaction and Axint drift by checking project memory, active sessions, and freshness, ensuring proof before long tasks or edits.Apache 2.0
- Save important information to long-term memory with tags, categories, and collections. Supports appending to existing memories and setting visibility for shared or private use.AGPL 3.0
- Retrieve stored information from long-term memory using semantic meaning, keywords, or both to provide context about topics when users ask questions.MIT
- Search long-term memory using natural language queries. Filter by tags, types, collections, and visibility to retrieve stored information from past interactions.AGPL 3.0
- Query fixed-rate borrow order history. Filter by orderId, currency, state, or term with cursor-based pagination.MIT
Matching MCP Servers
- Alicense-qualityDmaintenanceA persistent, self-organizing memory MCP server for AI assistants, using semantic search, knowledge graphs, and reinforcement learning to automatically manage and retrieve memories.Last updatedMIT
- Alicense-qualityFmaintenanceA persistent, human-like memory system for AI companions in LM Studio, using SQLite and ChromaDB for hybrid storage, enabling seamless recall across sessions and models.Last updated31MIT
Matching MCP Connectors
Persistent long-term memory for AI agents: semantic search, knowledge graph, and task canvas.
An interactive portfolio built for AI conversations. Browse work, services, and book calls.
- Reduce memory bloat by merging near-duplicate memories and summarizing related clusters into concise long-term memories. Compress episodic experiences into semantic knowledge.MIT
- Remove stored information from persistent memory by specifying its unique identifier to maintain accurate long-term context.MIT
- Promote a timeline episode to a persistent engram to preserve important session events for long-term memory.Apache 2.0
- Create a new context, either vector or memory, in a Lamatic project to store and retrieve data for AI workflows.MIT
- Promote a working-memory entry to long-term memory and tombstone the original. Supports decision (fully wired) and future skill/playbook stores.MIT
- Save a session close summary to retain context for the next conversation. Automatically promotes soon-expiring short-term memories to long-term storage to ensure continuity.Apache 2.0
- Store user preferences, decisions, and project context in long-term memory for recall across future sessions. Preserve technical specifications, coding conventions, and personal choices to maintain consistency.MIT
- Retrieve the athlete's full long-term coach memory, including PRs, goals, training context, and patterns, from stored markdown.MIT
- Save a conversation turn into long-term memory by curating topic, keywords, and typed links for a persistent concept graph.PolyForm Noncommercial 1.0.0
- Retrieve a ~300-character summary of a long-term memory chunk by ID. Use after recall to preview a relevant match before requesting the full text.Apache 2.0
- Trace the provenance of a long-term memory chunk to understand its origin, creation, and source material.Apache 2.0
- Deprecate outdated long-term memory chunks to keep recall results relevant. Flag incorrect or superseded information without deletion, with optional link to replacement.Apache 2.0
- Save important information from conversations into long-term memory to retain project preferences, coding conventions, and decisions across sessions.MIT
- Store information like facts, preferences, or events in MemoVault's long-term memory system for persistence across sessions.MIT