"A library or package named 'pubmedmcp@0.1.3'" matching MCP servers:

An MCP server that enables interaction with Markdown knowledge bases, allowing users to search and retrieve content by tags, text, URL, or date range from their local markdown files.

MCP server for searching and retrieving trading knowledge from a centralized SQLite library of book summaries, strategies, and document chunks.

Provides a 'library keeper' sub-agent that ingests PDF/EPUB books and answers questions grounded in them via local embedding search, with deterministic classification and knowledge gap logging.

Community-driven library of tested prompts for AI agents, enabling search, retrieval, sharing, and rating of prompts.

Enables Claude clients to access notes, guidance, projects, and search from a knowledge library, with explicit-save write tools for creating, updating, and appending content only when the user approves.

An MCP server that lets AI assistants add papers and books to your Zotero library by DOI, arXiv ID, or ISBN, and manage your collections, tags, and items.

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.

Provides token-efficient semantic search and document retrieval by indexing PDFs, text, and markdown files into local notebooks using ChromaDB. It enables AI agents to query relevant passages from large documents through local embedding models like Hugging Face or Ollama.

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.

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.

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

Enables AI agents to create, search, and manage subject matter expert profiles, including private workspace organization and moderated sharing to a common library.

MCP server for verified reuse infrastructure that lets agents query before work to obtain safe, permissioned results (exact component, source-free method, or abstention) with receiver-owned verification and non-disclosure guarantees.

Enables programmatic access to EndNote .enl libraries, allowing users to list, search, and extract full text from bibliographic references and their attached PDFs through MCP tools.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Enables fully local retrieval over a personal document corpus via hybrid search, cross-encoder reranking, RAPTOR summaries, and knowledge graph queries, served to AI agents over MCP.

A self-hosted MCP server for building a reusable AI-video reference library. It stores named Elements as structured reference images and provides them to MCP-compatible agents via @tags.

Project management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

Provides AI assistants with intelligent access to ML textbook content for creating accurate, source-grounded documentation using local models for privacy and cost efficiency.