"Pix" matching MCP servers:

A visual Retrieval-Augmented Generation MCP server that renders web pages, PDFs, and design screenshots into visual tiles and enables natural language querying over them via multimodal vision embeddings.

Enables searching and reading AVEVA Customer Support Portal knowledge base articles, including tech notes, known issues, and error-message diagnostics, to ground AI answers in support content not found in public documentation.

MCP server that gives AI assistants direct access to live AVEVA PI System documentation, eliminating hallucination on PI-specific topics by fetching real answers from the official docs.

Enables Claude Code to interact with Jupyter notebooks, perform semantic search over knowledge files, and manage research projects.

Personal Instagram Library — a read-only local MCP server that turns your Instagram saved posts into a private, AI-searchable knowledge base.

A workspace of six MCP servers—grounded-cv (hybrid RAG with citations), repo-intel (GitHub repo intelligence), web-research (safe web search/extraction), ats-jobs (unified ATS job boards), outcome-ledger (durable task ledger), and coding-workflows (code review & planning)—purpose-built for agentic hiring evaluations.

Enables AI agents like Claude to interact with Prometheux knowledge graphs and reasoning capabilities, allowing users to list and run concepts in their projects through natural conversation.

Enables Pi to use GZMO's curated memory system, providing tools for memory status, search, recall, and chain operations via MCP.

Enables AI assistants to record decision summaries when suggestions are rejected or corrected, and to search past decisions in later sessions so users do not repeat the same corrections.

Provides a cross-session memory system for AI assistants via MCP, with markdown-based storage, BM25 retrieval, and tools for writing, searching, reading, and managing memories.

Enables AI coding agents to search, read, create, update, and delete notes in a local Obsidian vault through hybrid semantic and lexical retrieval, with all embedding and vector storage running locally.

A Model Context Protocol server that enables coding agents to search for and record software issue fixes with semantic search using natural language queries.