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150,411 tools. Last updated 2026-05-28 05:14

"Understanding Persistent Memory and Context Management" matching MCP tools:

  • 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 relevant context from memory collections via search query, enabling outcome-based persistent memory for AI coding tools.
    Apache 2.0
  • Search persistent memory to find and return relevant facts based on a query. Supports AI agent memory recall.
    MIT
  • Append new entries to persistent memory for AI agents. Store market observations, trade records, and notes to maintain long-term context and recall.
    Business Source 1.1

Matching MCP Servers

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    A memory management system that enables AI assistants to store, search, and visualize persistent conversation contexts using a Neo4j graph database. It provides an MCP server for integration with Claude Desktop along with a web-based dashboard for managing relationship-based knowledge.
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    MIT
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    Enables AI assistants to execute shell commands and manage long-running processes within persistent tmux sessions across isolated workspaces. It features a dual-window architecture to separate raw command execution from interactive terminal output.
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    MIT

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

  • Store important context, decisions, and preferences in persistent memory that lasts across sessions. Categorize memories as context, preference, learning, work, or general for future recall.
  • Store key-value pairs in persistent memory to save user preferences, project decisions, and session context for future use.
  • Store and recall persistent memory across agents, sessions, and tools. Enable context retention and data sharing between different AI agents for consistent interactions.
  • Manage conversation sessions to maintain persistent context and memory across AI interactions, enabling continuity in multi-turn dialogues.
    MIT
  • List all context spaces you own or have access to, with memory counts returned as JSON.
    MIT
  • Save information like preferences, lessons, or project context to a persistent local database. Memories are retained across sessions and can be retrieved later.
    MIT
  • Store user facts, preferences, decisions, and context for persistent recall across conversations. Enables AI agents to remember important information through semantic search and knowledge graphs.
    MIT
  • Save key-value pairs to persistent memory across sessions for remembering user preferences, installed skills, or project context.
    MIT
  • Store memory observations with tags, importance, context, and optional auto-expiration. Persist AI agent knowledge with configurable TTL.
    MIT
  • Delete a specific memory by providing its unique ID. Removes unwanted or outdated memories from persistent storage.
    MIT
  • Remove stored information from persistent memory by specifying its unique identifier to maintain accurate long-term context.
    MIT
  • Store text information and metadata in a Qdrant collection for later retrieval, enabling persistent memory across sessions.
    Apache 2.0