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

Enables AI assistants to manage todo lists through natural language by creating, listing, updating, completing, and deleting tasks stored in Firebase Firestore. Supports custom system prompts for personalized task management workflows.

Enables LLMs to manage a todo list application through the Model Context Protocol, connecting directly to a browser-based Postgres database to add, list, complete, and remove todo items with categories, priorities, and due dates.

Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.

A simple MCP server for managing todo items with SQLite database storage, supporting add, list, and remove operations.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Enables interaction with Plaid's financial data API to sync bank transactions and retrieve account balances with secure encrypted token storage.

Enables Claude to manage todo lists with full CRUD operations including creating, listing, toggling completion status, deleting, and searching todos. Uses SQLite database with Prisma ORM for reliable data persistence and includes optional due date functionality.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

An MCP server for internal data platforms that enables search, viewing, tracing, and read-only querying of business assets like dashboards, metrics, and events.

A TypeScript-based MCP server that enables interaction with Azure Table Storage directly through Cline. This tool allows you to query and manage data in Azure Storage Tables.

A powerful Model Context Protocol (MCP) tool for exploring and managing different types of databases including PostgreSQL, MySQL, and Firestore.

Agent-First CRUD store MCP server — schema.yaml driven, SQLite backend, multi-table in a single daemon.

Enables AI models to interact with MySQL databases through MCP protocol, supporting queries, table schema inspection, and data manipulation operations.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Enables searching GitHub repositories, fetching readable web page text, and querying a local book database through MCP tool calls.

A Model Context Protocol (MCP) server that enables AI assistants to interact with MySQL databases by executing SQL queries and checking database connectivity.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

Deploys the Databricks AI Dev Kit MCP server as a Databricks App, exposing over 80 tools for interacting with workspace services like SQL warehouses, Unity Catalog, and AI/BI dashboards. It enables users to manage and query Databricks resources via natural language in the AI Playground using a Streamable HTTP transport.

Converts SQL queries between different database dialects using the sqlglot library to ensure cross-system compatibility. It allows users to list supported dialects and transpile SQL code from one syntax to another through the Model Context Protocol.