"Adobe Photoshop software and resources" matching MCP servers:

A TypeScript-based MCP server that enables users to query financial news, stock data, and index information while managing text notes with creation and summarization capabilities.

Enables synchronization and management of FoundryVTT journal entries within a Notion Story Bible, including media export and conflict resolution tools. It provides a Model Context Protocol interface for LLMs to preview, apply, and monitor data mirroring between tabletop RPG platforms and digital databases.

Enables AI agents and users to manage workspace files, monitor system metrics, take persistent notes, and retrieve weather data via MCP tools and resources.

Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.

MCP bridge for Inkra — drive a native macOS Markdown editor (SwiftUI + AppKit, not Electron) with live KaTeX/Mermaid preview from Claude, Cursor, or any MCP client. 18 tools across document editing, outline navigation, folder browsing, bookmarks, themes, and focus/wide view modes. Bridge open-source (MIT), Inkra app available on Mac App Store and direct download.

A NestJS-based server that enables AI agents to interact with Logseq graphs through its HTTP API for managing notes, journals, and blocks. It features specialized tools for project development tracking, including progress logs, technical decisions, and workflow prompts.

Enables local MCP clients to list, read, write, and search notes in an Obsidian vault via an HTTP server running inside Obsidian.

Provides AI clients with per-project todo management and persistent context notes via MCP, enabling task tracking and resume summaries.

A personal knowledge base MCP server that allows AI assistants to manage notes, tasks, and ideas through tools, resources, and prompts.

A bookmark management MCP server that enables saving, searching, and managing bookmarks with tags and read/unread status, providing tools, resources, and prompts for integration.

Enables AI assistants to read, write, and manage Microsoft OneNote notebooks, sections, and pages through OAuth-authenticated MCP tools, resources, and prompts.

MCP server for a personal notes/knowledge base that enables AI assistants to create, search, and retrieve notes using natural language. It exposes tools like create_note and search_notes, resources for each note, and a summarize_tag prompt.

This MCP server enables AI assistants to perform calculations, fetch live weather, manage in-memory notes, access system info and note resources, and use reusable code review and summarization prompts.

Enables AI assistants to read and write Memos notes through a Personal Access Token, with task-oriented search, precise editing, todo and tag management, attachment handling, exports, prompts, and resources. It supports both local stdio and multi-user Streamable HTTP transports, with safety switches such as read-only mode and restricted file access.

Enables everyday utilities like calculation, text analysis, encoding, hashing, UUID generation, datetime lookup, and note management through MCP tools, resources, and prompts.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

A minimal MCP server example demonstrating Tools, Resources, and Prompts. It enables calculations, time queries, note management, and code review prompts via stdio transport.

A minimal MCP server demonstrating tools, resources, and prompts for managing notes, with a simple notes app that supports adding, listing, deleting notes and summarizing them.

Enables listing, reading, and searching local Markdown notes through MCP tools and exposing them as context resources, with protection against path traversal attacks.

A local AI document assistant MCP server that enables listing, reading, and editing documents via tools, resources, and prompts, allowing LLMs to manage document workflows through natural language.