Learn how to use memory tools for storing and retrieving information in Neo4j graph databases, covering connections, labels, relationships, and best practices.
MIT
164,172 tools. Last updated 2026-05-31 02:42
"How to Manage AI Memory Effectively" matching MCP tools:
- Retrieve detailed documentation and examples for all API debugging tools. Understand how to use api_debug, api_login, api_config, and api_execute effectively.
- Manage conversation sessions to maintain persistent context and memory across AI interactions, enabling continuity in multi-turn dialogues.MIT
- Analyze your domain's citation frequency across AI platforms for up to 10 keywords. See where AI models reference your site to improve visibility.MIT
- View version history for stored data to debug past states, audit changes, or recover previous values in the Memstate AI memory system.Apache 2.0
- Lists all memory volumes (projects) accessible by your API key, each serving as an independent memory space for persistent memory management.MIT
Matching MCP Servers
- Alicense-qualityAmaintenancePersistent memory for any AI assistant. Zero token cost until recall. Stores memories in local SQLite, ranks by 6-factor scoring, returns results 79% smaller than JSON. Works with Claude, ChatGPT, Grok, Cursor, Windsurf, and any MCP client.Last updated22Apache 2.0
- AlicenseAqualityCmaintenanceProvides persistent session memory for AI assistants, enabling them to store, search, and retrieve conversation summaries across sessions via the Model Context Protocol.Last updated10MIT
Matching MCP Connectors
Cultural color and colour intelligence API. Every colour anchored to a named person, a documented year, and a consequence. 34 archives spanning literary, cultural, pigment, and national traditions. Ask it what color could get you executed in the Ottoman Empire.
Cloudflare Workers MCP server: agent-memory
- Fetch the complete AGIRAILS protocol specification to understand network operations, AIPs, and how to participate as a node.Apache 2.0
- Store memory observations with tags, importance, context, and optional auto-expiration. Persist AI agent knowledge with configurable TTL.MIT
- Inspect a memory's full lifecycle by providing its ID to see all events from creation through updates, recalls, links, and deletion. Understand why the memory exists and how it evolved over time.MIT
- Reinforce or deny a stored memory pattern by confirming when user validates or denying when they contradict it for accurate AI memory persistence.MIT
- Store or update a JSON value for a memory key with optional TTL, importance, source, and confidence score. Persists AI agent memory across sessions and changes.MIT
- Retrieve a breakdown of credit usage by feature and product scope, showing how credits are consumed across voice AI, voice models, and platform services.MIT
- View AI agents configured for automated WhatsApp Business message responses to manage customer interactions.MIT
- Create a new memory repository for AI agents. Supports private repos and organization ownership.MIT
- Manages conversation memory through hierarchical storage, adaptive retrieval, compression, knowledge graphing, inspection, and curation to maintain context integrity in long AI dialogues.MIT
- Delete a specific memory from the shared memory store using its ID. Helps manage and clean up persistent memories.MIT
- Fetch a ClawMem memory using an issue number or memory reference string. Retrieve specific stored data for your AI agent.MIT
- Store an atomic durable memory for AI agents. Requires detail; supports optional title, kind, and topics.MIT
- Access the complete Astria operating guide to learn available tools, recommended workflows, and best practices for persistent memory management.MIT
- Access detailed documentation for memory and config tools. Specify a topic to get instructions on using specific server features.