"Connecting Linear.app to manage software development tasks and structure" matching MCP servers:

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

MCP server for Coalesce that manages nodes, pipelines, environments, jobs, and runs, and enables project validation, DDL/DML preview, deployment planning, and cloud environment application.

An MCP server that scaffolds full-stack projects with consistent structure, Docker setup, CI/CD pipelines, and database configuration.

Enables AI assistants to perform defensive security tasks such as vulnerability detection, CVE lookup, phishing/link safety checks, and security report generation via MCP tools.

Enables AI agents to manage H-E-B grocery shopping tasks including product search, cart management, and coupon clipping through natural language.

Interactive feedback server for AI-assisted development with Web UI and desktop app support, enabling user feedback collection after AI tasks.

Enables LLM-driven agents to autonomously detect, diagnose, repair, verify, and prevent software and hardware failures on local and remote systems. Includes built-in safety checks and automatic rollbacks.

A local MCP server that lets any LLM agent manage Pine AI tasks — negotiate bills, cancel subscriptions, resolve disputes, and make phone calls on your behalf.

A Python MCP server that enables AI assistants to manage Todoist tasks and projects through the Model Context Protocol. It supports full CRUD operations for tasks and projects, including support for nested projects and Todoist's advanced filter syntax.

A FastMCP-based server providing a comprehensive toolset for the RunningHub AI application platform. It enables users to configure nodes, upload media, submit AI tasks, and manage task execution and results through persistent storage.

Obox MCP is a development toolkit that enables AI agents to autonomously execute system commands, manage files, and navigate projects within the IDE.

Enables LLM clients to inspect local development environment, including Docker container health, pnpm workspace integrity, and stuck process diagnosis.

An MCP server that enables Claude to manage Remember The Milk tasks, lists, and notes using natural language and Smart Add syntax. It provides full API coverage for task manipulation, including priority settings, tags, and undo support.

Orchestrates multiple AI coding agents declaratively to automate software development workflows for engineering teams.

Enables refining prompt intent, structure, constraints, and output instructions before prompts reach an LLM, with tools for schema retrieval, brief validation, and prompt variant generation.

Provides tools to search, download, and manage satellite imagery from all Copernicus Sentinel missions via the Copernicus Data Space ecosystem. It enables advanced geospatial queries, temporal coverage analysis, and automated data management for Earth observation tasks.

A template and demonstration project for building, testing, and deploying remote MCP servers using FastMCP and uv. It provides a foundational structure for creating MCP-compliant tools that can be hosted publicly and integrated with LLM agents.

MCP server integrating multiple Google Workspace services including Gmail, Calendar, Drive, Sheets, Docs, Tasks, People, Forms, and Slides, enabling users to manage emails, events, files, documents, and more through natural language.

Enables financial data retrieval, company context, market information, financial modelling, and valuation through MCP tools, with a deterministic sample provider for testing before connecting live data sources.

Enables connecting to multiple ClickHouse instances via dynamic registration or YAML configuration, supporting SQL queries and data source management through MCP tools.