Persist and retrieve semantic memory across sessions. Supports storing key-value entries, appending fragments, editing sections, and semantic search.
MIT
568,525 tools. Updated 2026-09-14 20:47
"memory" matching MCP tools:
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- Legacy dispatcher for backward compatibility; use add/search/list/update/delete/export/import/archive/restore/consolidate/stats to manage persistent AI context.Apache 2.0Destructive
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- Store and manage persistent facts across sessions. Add, view, update, or remove structured memories organized by sections like work, personal, and preferences.MIT
- Execute daily knowledge operations: recall, find, batch query, read, update, and arbitrate entries in a shared local SQLite store for AI coding tools.Apache 2.0
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Matching MCP Connectors
- memoryOAuth
Persistent long-term memory for AI agents: semantic search, knowledge graph, and task canvas.
Persistent agent memory paid per call via x402 USDC. Your wallet is your private memory namespace.
- Store and retrieve temporary key-value data during development workflows, supporting set, get, list, delete, search, and clear operations with tag-based organization.MIT
- Manages conversation memory through hierarchical storage, adaptive retrieval, compression, knowledge graphing, inspection, and curation to maintain context integrity in long AI dialogues.MIT
- Store project notes, recall context, search memories with hybrid semantic and keyword retrieval, cluster related items, deduplicate, archive old memories, and set permanent rules for persistent session intelligence.MIT
- Persist AI discoveries with save, recall, and search actions. Organize insights by category and retrieve by task or query.MIT
- Manage persistent shopping memory: read or write T1D config, preferences, and notes. Use get, set, or note actions to retrieve or update saved information.-
- Persistent key-value memory scoped to your wallet - agents remember across runs ($0.005 USDC per call)ConnectorNo auth
- Save, search, and manage long-term memories across conversations. Set preferences, facts, and skills; recall them later by topic.MIT
- Retrieve relevant memories from a markdown corpus using hybrid search, then answer state questions with latest, trace sequences with thread, verify git claims, and import external notes.MIT
- Search, browse and read back past sessions, decisions and reference docs from a local markdown corpus using hybrid retrieval, recency filters and thread context.MIT
- Retrieve, edit, promote, demote, or purge AI agent knowledge nodes while preserving learning state. Check accessibility state to ensure reliable retrieval.AGPL 3.0
- Set up a memory-bank directory and generate core files for structured project context tracking. Integrates existing project briefs and provides guidance for next steps. Uses a root directory path to initialize or overwrite files as needed.MIT
- Save, search, and delete project context or decisions across sessions using semantic memory. Store notes or decisions, find them by similarity, and clean up by ID, tags, or type.MIT
- Record, query, and validate domain knowledge using structured key prefixes like selector, tip, and avoid to maintain accurate automation contexts.MITDestructive
- Retrieve real-time Windows memory usage data including total, used, and available memory. Monitor system performance.GPL 3.0
- Retrieve statistical data on stored memories for the current codebase. Quickly assess memory usage and distribution to understand project context.MIT