"Understanding Persistent Memory and Context Management" matching MCP servers:

A self-hostable MCP server that provides permanent memory for AI agents using Postgres + pgvector for semantic search and Markdown file sync.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

MCP server for multimodal understanding and object grounding (bounding boxes) across images, videos, and documents, with support for multiple AI providers (Zhipu GLM-V, OpenAI GPT-4o, Anthropic Claude, or any OpenAI-compatible endpoint).

A zero-dependency Node.js playground for debugging how MCP clients authenticate to an MCP server over HTTP.

Enables persistent remote terminal sessions that survive dropped client connections, using pty-mcp and ai-tmux for interactive work and native OpenSSH for structured remote operations. Supports SSH config alias resolution, remote execution, file operations, and secure session management.

Integrates Xiaomi MiMo's multimodal API to enable understanding of images, audio, and video through natural language prompts.

Exposes employee leave-management operations (add employees, check balance, apply/cancel leave, view history) as MCP tools for AI clients like Claude Desktop to call directly.

Manages Supabase projects, databases, edge functions, secrets, and branches across organizations using the Supabase Management API with 24 tools.

Enables LLM agents to maintain structured long-term memory and knowledge using SQLite, with graph storage and relational query tools for persistent context.

Enables AI clients to read and write to a user-owned markdown bucket via S3-compatible storage, providing a persistent shared context layer across different AI tools.

Provides AI clients with per-project todo management and persistent context notes via MCP, enabling task tracking and resume summaries.

Provides AI agents with a single root terminal tool to a permanent Debian VPS, enabling them to run any Linux command, install software, manage services, and deploy applications that persist across sessions.

Persistent long-term memory for AI agents — semantic recall across Claude, Cursor, ChatGPT & MCP.

Connects AI assistants to your n8n instance to manage workflows, executions, credentials, and user settings through 31 specialized tools. It enables users to perform n8n operations like workflow creation, activation, and execution history retrieval via natural language.

Integrates Azure Cost Management APIs via MCP, enabling cost queries, forecasts, budgets, and Advisor recommendations through natural language in compatible clients.

MCP server providing deep PostgreSQL context to AI assistants, including schema DDL, index health, foreign key associations, query execution plans, and performance statistics via read-only tools.

Provides persistent context management for AI agents by storing and querying semantic information using Upstash Vector DB and Google AI embeddings. It enables semantic search, batch operations, and metadata filtering to help agents retrieve relevant stored knowledge.

An MCP server that provides AI assistants with persistent, semantic memory using Turso for storage and OpenAI for vector search. It enables natural language operations to store, retrieve, and refine information with automatic duplicate detection and quality validation.

An MCP server for unified cost tracking and analysis across AWS, OpenAI, and Anthropic. It enables users to query expenditures, compare costs across providers, and analyze usage trends through natural language.

Persistent project memory for AI models and coding agents. Memory MCP stores architecture, decisions, tasks, warnings, preferences, and session state in Supabase so OpenCode, Claude Code CLI, Qwen Code, Codex, or any MCP-compatible client can resume work without losing context.