"A tool or app for saving and editing todo tasks" matching MCP servers:

A Model Context Protocol server for AI agents to manage tasks and track progress across projects, with features like project isolation, search, and reporting.

MCP server connecting Claude/Cursor to Codex CLI, enabling code analysis via @ file references, multi-turn conversations, sandboxed edits, and structured change mode.

MCP server for Obsidian vaults — search, memory, link graph, 23 tools, OAuth-protected. Runs locally via Docker or remotely with Obsidian Sync + OAuth 2.1.

A task-board MCP server that provides tools to search, create, and update tasks, resources for reading the board, and prompts for standup and triage workflows.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

An MCP server for automating virtual or physical Android devices using the Gbox SDK. It enables users to manage app installations, capture screenshots, and perform complex UI actions through natural language instructions.

A Model Context Protocol server for the Quire project management platform, enabling AI assistants to securely interact with Quire projects, tasks, and data.

Enables AI assistants to automate mobile app testing and development for iOS and Android through natural language interactions. Supports intelligent element identification, session management, automated test generation, and comprehensive device interactions including clicks, swipes, screenshots, and app management.

A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.

An MCP server that enables AI assistants to directly control QGIS for tasks like layer management, feature editing, and map rendering. It provides a suite of 50 tools to execute processing algorithms and manage GIS projects through natural language commands.

Provides web automation utilities, including taking Camofox browser tab screenshots and saving them directly to local files.

Enables AI assistants to interact with KiCAD for PCB design automation, including schematic editing, component placement, routing, DRC/ERC, and export.

A flexible proxy server that aggregates multiple backend MCP servers into a single interface using STDIO or SSE transports. It supports dynamic server management via an HTTP API and utilizes namespacing to prevent tool conflicts across connected services.

A transparent proxy that intercepts high-risk tool calls and requires OTP-based human approval before they can be executed. It acts as a configurable circuit breaker between AI agents and target MCP servers to prevent unauthorized or dangerous actions.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.

Local MCP server for generating image assets with Google Gemini (Nano Banana 2 / Pro). Supports transparent PNG/WebP output, exact resizing/cropping, up to 14 reference images, and Google Search grounding.

Live Japan seasonal travel data from Japan Meteorological Corporation. 12 tools covering cherry blossom (sakura) forecasts, autumn leaves (koyo), fruit picking, flowers, festivals, and 3-day weather. 1,700+ GPS-tagged spots updated daily at 9AM JST. Works via npx or hosted HTTP endpoint — no auth required.

MCP server for Fizzy kanban task management with tools for boards, cards, comments, and checklists.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.