"iOS" matching MCP servers:

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.

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 bridge for PDF Content Search — full-text PDF search with Apple Vision OCR across thousands of documents in under a second from Claude, Cursor, or any MCP client. Advanced filters (date, category, sender, amount), wildcards, boolean operators. Bridge open-source (MIT), PDF Content Search app is commercial with free iOS+Android companion scanner apps.

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

An LLM-native decision tracking system that captures unexpected engineering outcomes as 'pressure events' to build a persistent learning foundation. It enables AI assistants to manage cases, log surprises, and promote recurring insights into global or project-specific knowledge bases.

MCP server that provides AI agents with persistent memory, cross-agent sharing, and context management, enabling them to remember conversations, track complex tasks, and evolve skills across tools.

Serves an AI coding agent a searchable index of a codebase's existing capabilities and past incidents, so it can find and reuse what already exists before writing new code. Also exposes blast-radius analysis for shared code and lets the agent reindex the knowledge base, all via local retrieval with no model calls or API keys.

Exposes the Integrated Memory System (IMS) capabilities, including session management, memory storage, and RAG-based context search, via the Model Context Protocol. It allows MCP-aware clients to interact with IMS backends to maintain long-term memory and context across sessions.

Enables safe local system command execution, file operations, hardware diagnostics, and persistent cross-session memory storage via SQLite.

Exposes AgentHive's member-level calls—including retrieve_context, log_session, create_agent, list_agents, create_task, and list_tasks—as native tools for Cursor and Claude Code. It lets IDEs spawn a stateless local subprocess that makes plain HTTP calls to an existing AgentHive instance, so agents can retrieve reviewed team memory and log sessions without hand-written HTTP instruction blocks.

MCP server that lets agents create and update persistent concept maps via the NodeLand API, returning shareable URLs for humans to view, embed, and keep editing.

Stops AI agents reopening rejected decisions and forgetting project state. Persistent operational state for agents: decisions, plans, blockers, priorities and patterns that survive across sessions, with enforcement. Not conversation logs.

An MCP server that allows AI assistants to search and retrieve human-curated content recommendations from Copus.

Enables code agents to persist and recall durable project knowledge — rules, decisions, procedures, learnings and secrets — across sessions at low context cost, with accent-insensitive PT-BR search, scoped per repository/workspace, and secrets that stay out of the model's context.

Provides persistent, decay-aware memory for AI applications by integrating the Smara Memory API through semantic search and Ebbinghaus forgetting curves. It enables tools to store, search, and manage long-term user context with importance-based ranking and automatic decay.

An open-source server implementing the Model Context Protocol (MCP) that enables capturing insights from AI sessions and transforming them into persistent, searchable knowledge accessible across tools.

MCP server that provides a shared semantic memory layer for AI coding agents, enabling teams to store, search, and sync context, decisions, and knowledge across projects with project-based isolation and multi-backend support.

Provides access to the HUMMBL Base120 framework of 120 validated mental models organized across 6 transformations, enabling users to search, retrieve, and get AI-recommended mental models for problem-solving and decision-making.

XMemo is a secure, user-owned memory substrate and context engine for AI agents, CLIs, IDEs, and LLM workspaces. Exposed over Streamable HTTP MCP, it empowers agents with cross-session memory, task continuity, and personalized context. Key Features: * Personalized Context: Stores and recalls developer preferences, project guidelines, and coding patterns via semantic vector search. * Agent Daily Me

MCP server for StudioMeyer Academy that connects Claude Code, Cursor, or Claude Desktop to track learning progress in the Memory-First AI Operator curriculum. It enables users to view lessons, complete quizzes, earn certificates, and run spaced-repetition reviews directly in chat.