"Information about iOS development with Xcode" matching MCP servers:

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.

Memory bank with Server as SSH support for central knowledge base

Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.

A local MCP server for Claude Desktop with persistent task management, file operations, document generation, and PDF indexing.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

Enhances user interaction through a persistent memory system that remembers information across chats and learns from past errors by utilizing a local knowledge graph and lesson management.

Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.

Connects Bear Notes to AI assistants using semantic search and RAG (Retrieval-Augmented Generation), allowing AI systems to access and understand your personal knowledge base through meaningful search rather than just keyword matching.

A multi-agent AI tutor that delivers personalized lessons, resolves doubts with RAG, generates quizzes, and tracks progress, all accessible via MCP for Claude Desktop.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

Enables users to query weather, perform web research, and manage a graph database through natural language.

Enables ingesting documents or text to extract entities and relationships via LLM, storing them in Neo4j, and searching or retrieving episodes.

A powerful context management system that maintains persistent context across coding sessions, helping development teams track project structure, dependencies, and progress.

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

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Public, agent-searchable knowledge base about AI-native software development, served as an MCP server with tools to search, read, and list topics.

A local MCP server that maintains a persona profile (contact library) for AI assistants, allowing them to create, search, retrieve, supplement, and correct information about people mentioned in conversations via tools like search_profiles, get_profile, create_profile, update_profile, add_facts, update_fact, and delete_fact.

A personal knowledge hub MCP server that enables LLMs to query structured information about Akib Dabgar's skills, experience, projects, and goals using Dynamic Context Retrieval for efficient context usage.

Gives AI coding agents persistent, evolving knowledge about a codebase, enabling them to store and retrieve observations about architecture, conventions, gotchas, and recent work context.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.