"Information on Vision Pro" matching MCP servers:

The most feature-complete MCP server for Obsidian vaults. 23 tools and 3 resources for search, read, write, tags, link analysis, graph traversal, and canvas support.

Non-custodial memory MCP server with client-side encryption, enabling secure remember, recall, forget, and share operations with post-quantum security.

AutoMem MCP provides persistent memory for AI assistants, enabling them to recall information across conversations and platforms with graph-vector retrieval.

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.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.

45-tool MCP server for video analysis, deep research, content extraction, web search, and Weaviate knowledge storage. Powered by Gemini 3.1 Pro.

A full-featured long-term memory system for Claude Code that persistently stores and retrieves preferences, decisions, and project context across sessions using hybrid search and LLM-powered extraction.

Provides persistent, searchable memory for AI agents, enabling them to retain, recall, and reflect on information across conversations.

An MCP server that provides semantic memory on top of Qdrant vector search, with tools to store and retrieve information using embeddings.

Enables storing and retrieving text passages based on semantic meaning using local embeddings (Ollama) and vector storage (ChromaDB), allowing conversational memorization and retrieval of information.

A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

Persistent visual cache for LLM-driven software development. Caches screenshots using perceptual hashing, vector search, and AX trees to prevent token overhead and visual hallucination loops.

Enables seamless integration between Claude and Dry smartspaces, turning conversations into persistent, structured data by creating memories and querying information.

An MCP server that bridges local Ollama models and ChromaDB vector memory to MCP clients like Claude Code. It enables local text generation, vision-based image analysis, and semantic memory storage without requiring external API keys.

MCP server for querying the DodaOne governance framework, enabling users to retrieve governance information and evaluate proposed actions.

A persistent memory layer for AI tools that decouples personal data from AI's unstable memory, enabling you to mention information once and have it remembered forever across all conversations.

Enables MCP clients to remember user information, preferences, and behaviors across conversations using vector search technology. Built on Cloudflare infrastructure with persistent storage and semantic similarity matching.

Enables source-first orchestration and knowledge indexing with inspectable architectural capabilities through a unified MCP interface, including named-attribute retrieval and atomic knowledge ingestion.