"Vim" matching MCP servers:

Enables AI agents to consume 50+ NVIDIA NIM models including LLMs, image generation, and vision through 10 MCP tools with rich metadata and advanced filtering.

MCP server that provides web search functionality using the Tavily API. It runs in stdio transport mode and can be integrated with Cursor or other MCP clients.

Enables offline CRUD and semantic search on Wikipedia ZIM archives via MCP tools for reading, writing, editing, deleting, and searching articles.

Enables AI agents to access 140+ NVIDIA NIM models for chat, embeddings, reranking, vision, image generation, OCR, and content safety via stdio.

Enables interaction with .zim archives by providing tools for article search, content retrieval, and metadata discovery. It features a TF-IDF based RAG engine for semantic retrieval over extracted article chunks from compressed ZIM files.

Enables searching and retrieving Claude Code conversation history that would otherwise expire after 30 days. Supports full-text search, semantic search, and session management with automatic backup of all conversations.

Enables grounded read-only queries over a local knowledge base, reviewable pending updates, and audited merging of changes.

Enables storage and semantic search of facts, and interactive 3D visualization of embeddings via MCP tools.

A local academic research assistant that indexes PDFs into a searchable vector library and exposes MCP tools for semantic search, claim extraction, contradiction detection, and multi-step research synthesis.

An educational interaction management system that uses MCP and Ollama to create and manage flashcards and other learning content. It enables dynamic content generation and transformation through natural language processing using local AI models.

Provides authenticated access to PostgreSQL databases for Claude AI, enabling users to browse database tables, discover schemas, and execute custom SQL queries through natural language interaction.

Enables AI assistants to query a person's CV and portfolio content via MCP tools and resources, returning grounded answers from local markdown data instead of relying on resume parsing.