"Papers With Code" matching MCP servers:

An AI-powered research assistant that integrates with Zotero to read academic papers, create intelligent annotations, and generate structured notes. It enables users to highlight findings, explain formulas, and write comprehensive summaries directly within their Zotero library through natural language commands.

This MCP server provides tools to search arXiv, score papers for relevance and citation impact, and find foundational references, enabling research assistants to compile reading lists.

Connects your Zotero research library with Claude and other AI assistants via the Model Context Protocol, allowing you to search your library, access content, discuss papers, get summaries, and analyze citations.

A lightweight MCP server that connects AI agents to a local Zotero library for paper management and metadata retrieval. It enables users to search titles and abstracts, browse collections, and automatically ingest papers via arXiv ID or DOI with PDF attachments.

Control Apple Music via natural language from Claude Code, with the ability to mark tracks and accumulate reactions in an Obsidian Vault.

Local-first MCP server for working with an Obsidian vault. No API key required

A server that enables MCP clients like Anthropic Claude App to interact with local Zotero libraries, allowing users to search papers, manage notes, and access research materials through natural language.

Enables AI assistants to interact with Coda docs, pages, tables, rows, formulas, and more via the Coda API, offering 54 tools, 12 resources, and 5 prompts for comprehensive document management.

An academic research tool that enables users to search across nine major paper sources, rank results with AI-driven criteria, and automate paper notifications to multiple platforms. It streamlines literature management through integrated support for Zotero, Obsidian, and personal library website generation.

Enables Codex to search, create, and organize notes in Simple Sticky Notes 6.9 on Windows via MCP, with support for rich text formatting and safe write operations.

An MCP server that connects AI coding agents with Apple Notes for developer workflows like capturing debug sessions, logging commits, and saving code snippets.

A read-only MCP server for interacting with Coda API, enabling listing documents, pages, tables, rows, and retrieving page content as markdown.

Personal memory MCP server for Claude Code with an Obsidian-style graph. Enables persistent, queryable memories across sessions using Markdown files with bidirectional wiki-links and a D3.js force-directed graph UI.

Gives MCP clients a local, single-tenant SQLite-backed store for saving, searching, bootstrapping and recalling memory records, plus saving and loading session handoffs, using text search by default with optional embeddings. It runs over stdio or an authenticated loopback HTTP gateway with explicit-confirmation pruning, scoped policies, and admin-driven backup, restore-copy and restart-drill verification.

Notion API MCP server for Claude Code to manipulate Notion pages, blocks, and databases with batch operations and Windows compatibility.

A Model Context Protocol server that implements a simple notes system, allowing users to create, list, and summarize text notes.

Enables interaction with Apple Notes via natural language, supporting note creation, search, and retrieval with iCloud integration for seamless note management.

Enables Claude to search your team's design and issue comment threads from Figma, Jira, and Notion, answer questions with citations, surface feedback relevant to the code you're editing, and post replies or close threads after your confirmation.

Enables AI apps like Claude, ChatGPT, Copilot, Claude Code and Codex to read and write a shared company wiki over MCP, where meetings, work sessions and notes become living pages about people, projects and decisions. It also serves search, briefs, transcripts, decisions and action items, and lets teams connect their own git-hosted team wiki.

Enables searching arXiv papers in Korean, Chinese, Japanese, or English and saving findings to a local Markdown vault through natural language commands.