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"General Information or Concepts Related to Memory" matching MCP servers:

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    Failure Memory provides AI coding agents with a shared local memory of failures, enabling them to record, recall, and learn from mistakes across sessions.
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    MIT
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    Governed multi-agent memory for AI agents. Hybrid markdown + SQLite store with full-text search, vector retrieval, and LLM reranking. Three transports: MCP stdio, HTTP JSON-RPC, and MCP SSE. One Go binary
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    Apache 2.0
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    🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vector search, semantic knowledge storage, and efficient relationship management - perfect for AI agents and knowledge graph applications.
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    MIT
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    A memory, docs, and repo context layer for engineering agents, providing typed persistent memory, RAG document retrieval, and repository-aware tools to recall decisions, runbooks, and operational knowledge across sessions.
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    MIT
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    An MCP server that provides persistent memory for AI agents, enabling context retention across sessions and supporting vibe-loop workflows where agent promises and deliverables are tracked and validated.
    MIT
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    Local-first, file-based memory layer for AI agents — one shared Markdown vault across Claude, Codex, Gemini, Cursor and any MCP client. Provides read/write memory tools with an audit trail, per-agent trust levels, and Git sync; no cloud and no lock-in.
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    MIT
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    Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.
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    MIT
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    A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.
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    An MCP server that gives AI agents persistent, narrative memory: concepts as nodes, relationships as typed "because" edges, so anything filed can be pulled back by association rather than by address.
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    MIT
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    Provides AI coding assistants with code search, impact analysis, task chaining, and persistent memory to turn AI demos into deliverable code.
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    MIT
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    MCP server that helps coding agents research and prepare GitHub contributions by gathering repository guidance, related work, code context, and validation evidence into a local SQLite corpus, without ever writing to GitHub.
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    MIT
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    Connect any AI client to the CaBrain memory system via MCP, exposing tools for memory recall, retain, and brain management.
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    MIT
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    MCP server for Lightpanda headless browser enabling ultra-fast HTML extraction, markdown conversion, and JavaScript execution with 16x lower memory footprint than Chrome.
    MIT
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    A native, local-first, multilingual memory server for Codex, Claude Code, and any MCP client, providing hybrid semantic and exact memory recall using Go, Qdrant, and bge-m3. It enables stable, concurrent memory storage and retrieval without Docker or cloud dependencies.
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    MIT
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    The Time MCP Server is a Model Context Protocol (MCP) server that provides AI assistants and other MCP clients with standardized tools to perform time and date-related operations. This server acts as a bridge between AI tools and a robust time-handling back
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    MIT
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    A secure and pluggable MCP server to run terminal commands on your local machine or cloud server — remotely, safely, and with LLMs or agentic clients.
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    ContextLattice is an HTTP-first, MCP-compatible memory/context/task orchestrator that persists writes and returns fused recall from specialized stores with local-first defaults. Primary URL: https://contextlattice.io/ Install: https://contextlattice.io/installation.html Troubleshooting: https://contextlattice.io/troubleshooting.html
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    Apache 2.0