"A real-time voice and text AI assistant with Google Search integration and system control" matching MCP servers:

Enables users to directly edit authoritative Markdown context and tables within Codex, review the complete text before saving, and commit tracked immutable revisions with version history.

Enables AI-powered knowledge management and creative support by connecting Scrapbox data to Claude. Supports advanced search, relationship analysis between pages, theme extraction, and literary analysis of personal knowledge bases.

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.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables MCP-capable AI clients to read and write structured, project-scoped memory through a Cloudflare Worker backed by D1 and R2.

Analyses your published writing from a sitemap, extracts a corpus, and generates a Claude Skill so Claude writes in your voice.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

Read-only MCP server that exposes locally generated voice notes to any MCP client, allowing listing, searching, and reading transcripts, summaries, and knowledge graphs from voice-notes sessions.

A research assistant server that enables saving, organizing, and retrieving research content with semantic search using ChromaDB and OpenAI embeddings.

Local-first knowledge system for reasoning agents, exposing facts, evidence, documents, retrieval, and audit history through a thin stdio MCP server.

Enables MCP-compatible AI clients to store and recall voice conversation context by caching user and AI utterances, supporting formatted context summaries for multi-turn voice interactions.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

MCP server for NodeBB forums that enables AI assistants to access forum data, search topics, and perform semantic search via the Model Context Protocol.

Enables real-time auditing of LLM long-term memory to detect contradictions, user-introduced falsehoods, staleness, and unsourced fabrications, while providing a safe memory store with tools like recall, review, and restore.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Implements the Model Context Protocol to retrieve context from a locally running Llama model, enabling AI applications to query and receive relevant information.

MCP server that indexes your Obsidian notes into a Milvus vector database and enables querying them via a local or OpenAI LLM, with real-time synchronization.

Enables Claude to act as a personal assistant in Telegram by providing tools to read new messages, send replies, and manage tasks/reminders/notes in a Supabase-backed memory.

MCP server that connects Claude to a Telegram personal assistant, enabling message processing, task management, and responses via scheduled workflows.

Enables AI assistants to maintain persistent conversations and context between sessions through automated saving and global installation across projects. Provides zero-configuration memory persistence with automatic conversation history preservation.