"A production-ready Task Management MCP server for AI agents and autonomous workflows" matching MCP servers:

A production-grade MCP server and client implementation with comprehensive features including structured logging, health checks, metrics, authentication, and RAG capabilities with PostgreSQL vector search. Supports both stdio and SSE transports with containerization and security features for enterprise deployment.

A production-ready MCP server that enables users to interact with Neo4j databases through health checks and Cypher query tools. It features a structured, containerized architecture with built-in support for Azure deployments and environment-driven configuration.

Enables MCP clients to discover and execute operational tools such as database mutations and system diagnostics over stdio, with deterministic structured outputs and Langfuse observability.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Provides FastMCP-based servers with various tools for AI assistants including math operations, file management, note-taking, todo management, and database operations. Offers both basic and advanced server configurations with tools, resources, and prompt templates.

Manages Supabase projects, databases, edge functions, secrets, and branches across organizations using the Supabase Management API with 24 tools.

Provides specialized tools for portfolio health analysis, rebalance simulations, and trade execution via a single interface powered by MongoDB. It enables AI agents to manage investment portfolios while adhering to organizational governing rules, clearance guards, and rate limits.

Enables AI agents to inspect, query, test, and safely fix dbt projects and BigQuery warehouses under policy-enforced controls, with read-only direct queries and dbt-only allowlisted writes.

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

Enables local data discovery by indexing metadata from SQLite, CSV, and Markdown sources, providing hybrid keyword and TF-IDF semantic search via MCP tools (listSources, indexSource, search, getSchema) and a REST API.

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.

A local Model Context Protocol server providing backend tools for AI agents to manage projects and tasks with persistent storage in SQLite, enabling structured tracking of project tasks with dependencies, priorities, and statuses.

MCP server for Metabase that gives AI agents full access to query, explore, and manage content in your Metabase instance.

Centrally manages Claude agent definitions, configurations, and custom commands across multiple devices using a SQLite database, eliminating file synchronization conflicts and enabling live updates across all connected Claude sessions.

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

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

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 role-based order management through MCP tools, allowing users to view and refund orders according to their permissions (USER, MANAGER, ADMIN) with audit logging and JWT authentication handled by a FastAPI client.

Enables managing daily work logs with tools for adding, listing, updating status, deleting, and summarizing tasks, using SQLite for persistent storage.

Enables CRUD operations on a SQLite task database with filtering by status and priority.