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

A lightweight memory layer for MCP servers that persists user context across LLM sessions with minimal token cost, supporting key-value dedup, multi-tenant namespaces, and optional TTL.

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

A local semantic memory and code-indexer that uses AST parsing for structural understanding and persists architectural decisions to help AI assistants bypass context window limits.

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

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).

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

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

A local-first MCP server providing persistent, searchable knowledge base via SQLite, enabling AI agents to save and recall facts across sessions without cloud dependencies.

Enables AI agents to maintain a structured Markdown or Obsidian memory vault with tools for reading, writing, searching, and organizing notes.

Enables LLM assistants to store, retrieve, and update user-specific context memory including travel preferences and general information through a chat interface. Provides analytics on tool usage patterns and token costs for continuous improvement.

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

A Model Context Protocol server that gives AI assistants persistent, scoped memory by saving and retrieving short notes (mementos) across sessions and projects, enabling dynamic learning and context injection without heavy dependencies.

Persistent AI memory with SQLite hybrid search (FTS5 + semantic), built-in Qwen3 embedding, and rclone sync across machines.

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.

Provides Claude Co-work with MCP tools to search and record organizational memory, including search, read, query, ingest, remember, sync, and status operations.

MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.

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

Creates and maintains a semantic knowledge graph of code that allows maintaining context across sessions with Claude, providing advanced search capabilities without requiring the entire codebase in the context window.

Enables role-based order management operations such as viewing orders, checking refund eligibility, issuing refunds, deleting orders, and managing users through MCP tools with audit logging and permission checks.

Enables AI development tools to maintain context across chat sessions with automatic branching, progress tracking, and TODO management for different tasks.