"The term pHqghUme" matching MCP servers:

Provides long-term memory for agents with meaning-based recall, evidence-gated writing, and separate stores per agent mode.

Agent-agnostic persistent memory backend. 13 MCP tools, Supabase + Jina embeddings, multi-profile isolation, semantic recall across sessions.

An MCP server that provides long-term memory and semantic search using Qdrant and OpenAI embeddings, with tools for storing, searching, and managing knowledge.

MEMANTO is a memory agent. It remembers, recalls, and answers - so your agents can achieve long-term goals and avoid confusion.

Enables AI applications to add, search, update, and delete long-term memories using the Mem0 Memory API, allowing agents to persistently remember user preferences, conversation history, and contextual information across sessions.

A fully local MCP server that gives AI agents persistent, semantic long-term memory without any cloud dependencies.

Enables persistent long-term memory for Claude Code across sessions, with tools for storing, searching, and managing facts, knowledge graphs, and procedural lessons.

A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.

Provides long-term memory capabilities for MCP clients by wrapping the Mem0 API, enabling semantic search, storage, retrieval, and management of conversation memories across users and agents.

Provides OpenCode with adaptive long-term memory by storing preferences, lessons, and usage history locally in SQLite, enabling AI to remember and adapt to users through context-based learning.

Provides tools to fetch and search news from The Verge's RSS feed, allowing users to get today's news, retrieve random articles from the past week, and search for specific keywords in recent Verge content.

Persistent, graph-powered memory for AI agents that provides long-term semantic recall using a local Kuzu graph database.

An open-source bitemporal knowledge graph that provides long-term memory for AI agents via a native MCP endpoint, enabling conflict-aware ingest and hybrid retrieval.

Provides persistent memory for AI models by enabling the storage and retrieval of episodic, semantic, and procedural information through the memro protocol. It allows assistants to maintain long-term context via semantic search and chronological memory management.

An MCP server that gives Claude-based agents persistent long-term memory with semantic search, BM25 hybrid reranking, associative recall, episode grouping, and sleep consolidation.

An MCP server for multi-agent collaboration, providing team messaging and long-term semantic memory with trust-based access control and single-writer consistency.

Provides a local-first memory layer for coding agents, storing principles, rules, and corrections on-device and surfacing them at the moments they apply so agents act on the intended outcomes without sending data to the cloud.

Markdown-first long-term memory for AI coding agents, enabling hybrid search over local files via MCP tools.

Provides fully local long-term memory for AI agents by enabling semantic search over notes and session logs using Ollama embeddings, with no external APIs or databases.

Provides persistent long-term memory (semantic RAG) for AI coding assistants, enabling them to store and semantically search code and documentation across chat sessions without token limits.