"Information on memory" matching MCP servers:

Local-first cross-agent memory MCP. 6-layer structured brain (goal/context/emotion/impl/caveat/learning) with token-saving file diff cache (86% measured savings on re-reads)

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

MCP server that exposes the OBBBA No Tax on Tips federal deduction logic as callable tools, enabling users to check eligibility and estimate tip deductions.

Multi-user, file-backed MCP memory server enabling isolated namespaces and persistent memory across sessions and AI clients.

Enables keyword search, filtering, and retrieval of Claude Code memory files, reducing context overhead by fetching only relevant memories on demand.

A zero-dependency, file-based persistent memory system for AI agents with tiered memory, Ebbinghaus decay, and keyword retrieval.

Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.

A Model Context Protocol server providing durable, cross-session memory for AI agents, powered by Qwen on Alibaba Cloud. Enables agents to write, search, recall, and forget memories with semantic ranking.

Persistent memory and payment safety for AI agents on Lightning. Enables agents to remember purchases, track vendor reputations, enforce budgets, and share trust signals via Nostr.

Provides persistent memory for Claude with hierarchical categorization, cross-corpus recall, session journals, and customizable persona, enabling memory continuity across sessions.

An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.

A simple memory system that allows LLMs to store and retrieve information via the Model Context Protocol.

Persistent memory MCP server for AI agents, using SQLite with hybrid keyword and semantic search for long-term memory storage.

A knowledge graph memory server using SQLite to provide persistent, isolated contexts for organizing information into searchable categories like work and personal projects. It features unique ID-based operations and a token-efficient serialization format designed to optimize interactions with LLMs.

Provides persistent memory with semantic search for MCP-based AI agents, enabling them to store and recall information across sessions using vector embeddings.

Enables AI agents to record and rank learnings, facts, and methods through a collaborative voting framework. It provides tools for agents to surface the most useful information across sessions using persistent memory storage.

Enables AI assistants to maintain persistent project context across sessions by storing and retrieving structured information in markdown files organized in a memory bank directory.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

An implementation of a classification-based persistent memory system that enables Claude to store and retrieve classified memory information across chat sessions

A custom Memory MCP Server that acts as a cache for Infrastructure-as-Code information, allowing users to store, summarize, and manage notes with a custom URI scheme and simple resource handling.