"Multi-Agent Systems with Shared Memory Storage" matching MCP servers:

Enables AI agents to share persistent memory via an MCP server using SQLite, supporting multi-tenant, categorized knowledge with TTL and semantic links, without requiring vector databases.

A portable, self-hosted semantic memory layer for LLM agents, enabling them to search and add memories by meaning over the Model Context Protocol.

MCP server providing persistent memory management for AI agents using SQLite and FTS5, enabling storage, full-text search, and recall of memories with namespace isolation.

Provides a local markdown-based memory system for coding agents through MCP, enabling search, add, register, inventory, sync, and ingest operations across user and project memory. It gives any agent tool a durable, provider-agnostic shared memory stored in folders you own.

A powerful MCP server for Excel operations with seamless Supabase Storage integration.

Transforms your IDE into an autonomous multi-agent coding assistant that orchestrates complex codebase refactoring using LangGraph and LiteLLM.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

AI-powered VMware storage management for vSphere. Manage datastores, iSCSI targets, and vSAN via natural language with 11 MCP tools.

Enables agents to manage persistent long-term memory through MCP tools for searching, adding, updating, giving feedback, and forgetting memories, with automated pipelines for redaction, distillation, and reconciliation.

Manages multiple AI CLI instances (Claude Code, Codex, Gemini, Cursor) in tmux sessions for parallel task execution, with optional git worktree support.

An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.

Provides long-term memory for AI agents with per-user scoped recall, ranking by relevance, recency, and importance, consolidation of repeated events, and automatic forgetting.

Standalone memory microservice that converts completed agent sessions into long-term memory and exposes retrieval through an MCP tool interface, enabling agents to search their past interactions.

Provides local-first, project-aware durable memory for coding agents, with a human-reviewed Markdown vault, MCP daemon, and dashboard for managing and retrieving shared knowledge.

MCP server for zero-config, traceable long-term memory using SQLite, enabling agents to store, search, trace, and monitor memory with tools like memory_store, memory_search, and memory_health.

Provides 7 tools for weather (geocoding, current conditions) and country data (capital, currency, population, dial code, flag) via Open-Meteo and CountriesNow APIs, designed for multi-agent AI systems.

Provides a shared long-term memory across multiple AI clients, enabling persistent storage and retrieval of facts, preferences, decisions, and snippets with semantic search.

Provides persistent, inspectable memory storage for AI agents using SQLite. Agents can store, recall, and search memories across sessions via three MCP tools.

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-native, local-first memory for coding agents that turns real sessions into reusable decisions, gotchas, and domain knowledge.