"A local AI setup with LM Studio and a secure browser for real-time AI searches" matching MCP servers:

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

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.

An MCP (Multi-Agent Conversation Protocol) Server that provides access to Google's Real-Time Bidding API, enabling programmatic interactions with RTB functionalities through natural language.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

A simple AI development tool that helps users interact with AI through natural language commands, offering 29 tools across thinking, memory, browser, code quality, planning, and time management capabilities.

Enables MCP clients to interact with local LLMs via LM Studio, supporting dynamic chat, vision, RAG, file interaction, and model orchestration.

Generates production-ready short video scripts from real-time web search data using Tavily and Gemini, exposed as MCP tools.

A proxy server that sits between MCP clients and servers, providing authentication, tool discovery, caching, and guardrail enforcement to protect MCP servers from malicious inputs.

Open-source AI memory layer for LLM agents. Importance scoring, temporal decay, hierarchical memory (facts, summaries, themes), YMYL prioritization, and active retrieval with contradiction detection. Supports OpenAI, Anthropic, Ollama. Local-first with SQLite + FAISS.

MCP server that enables AI-powered content generation in multiple formats using Google Gemini and Tavily real-time research, accessible via MCP-compatible clients.

Enables AI coding agents to persist and retrieve project knowledge using three MCP tools with local vector and full-text search.

Persistent memory for any AI assistant. Zero token cost until recall. Stores memories in local SQLite, ranks by 6-factor scoring, returns results 79% smaller than JSON. Works with Claude, ChatGPT, Grok, Cursor, Windsurf, and any MCP client.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables searching, indexing, and recovering past AI chat sessions and agent actions from local AI coding tools, with optional vector database semantic search and direct filesystem access.

Integrates with the Datalog Studio REST API to explore projects, tables, and assets within a workspace. It enables users to understand data schemas and upload plain text content directly for AI processing.

Enables natural language queries over financial reports, with multimodal retrieval across text, tables, and charts via an agentic RAG system.

An AI apprentice system that allows users to train AI through demonstration, correction, and review, with structured task execution and emphasis on packaging design workflow.

Enables Claude Code to search and retrieve from a local knowledge base of markdown notes using hybrid semantic+keyword search, keeping data entirely offline.

Spring AI Playground is a self-hosted web UI platform for building low-code tools and dynamically exposing them via built-in MCP server for AI agents.

Generates a complete suite of AI readiness files (llms.txt, ai.txt, schema, RAG indexes) for any website to optimize representation in ChatGPT, Claude, Gemini, and Perplexity.