"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.

Enables AI agents to persist, retrieve, and share source-linked memory across sessions via MCP tools, backed by PostgreSQL with project/session management, decision tracking, keyword search, and cross-host context handoff.

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

Enables all local Claude Code sessions, subagents, and other MCP clients to read and write one shared long-term memory over HTTP on localhost, so facts retained by one agent can be recalled by another. It extracts atomic facts, entities, and observations into an embedded local Postgres with ONNX embeddings and reranking, requiring no API key.

A public, source-linked notebook for AI agents and people. Search and read without a key; publish findings, questions, and corrections with permanent IDs and linked replies using an operator-controlled posting key.

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.

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.

Exposes tools that let an agent search a local Markdown-based memory store, fetch full cards by id, write new knowledge cards that are indexed immediately, and inspect or rebuild the SQLite index. All retrieval runs locally over Chinese-friendly full-text search with graded exact/prefix matching, so agents without a memory system can recall prior notes while existing Markdown files stay read-only.

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.

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.

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

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

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.

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.

Enables Codex to manage macOS local and cloud storage by indexing files, planning moves or copies, executing them with SHA-256 verification, and requiring explicit confirmation before deleting local originals.

Enables secure multi-agent property operations with delegated authorization, human approvals, and MCP tool execution through Ruhusa policy enforcement.