"Automating Task Assignment Based on Priority with Reshuffling Capabilities" matching MCP servers:

Enables MCP-based integration with the Priority ERP OData REST API, with strict environment validation and a read-only default. As of the current README, no tools are registered yet; the server only boots and waits on stdio.

An MCP server that exposes Priority ERP's OData operations (query, create, update, delete, batch, attachments, text fields) as 19 tools for AI assistants like Claude. It supports Streamable HTTP transport with OAuth 2.1 and two-layer authentication (bearer token plus Priority credentials).

Enables prioritizing vulnerabilities by real-world exploitation evidence, combining CISA KEV, EPSS, CVSS, and SSVC to rank CVEs and package versions, and providing fix recommendations.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

Enables alarm investigation through MCP tools for asset search, metadata lookup, alarm retrieval, summarization, priority scoring, and operator recommendations, with RAG-backed evidence from procedure documents.

Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.

Elevate your LLM task management with Task Orchestrator, an MCP server that empowers you to define, organize, and track goals and tasks with hierarchical precision. Integrate intelligent task management into your workflow.

A task management system for LLM-based agents that stores all tasks in a single tree, available immediately after the server starts.

Provides an MCP server that tracks open loops (pending decisions or replies) across email, agent sessions, and other channels, enabling agents to query what is waiting on whom.

A Model Context Protocol implementation that provides a standardized interface for task management, supporting both STDIO mode for CLI/AI applications and HTTP+SSE mode for browser-based clients.

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Enables users to manage tasks through a simple JSON file interface. Provides basic task management functionality by reading and writing to a configurable tasks.json file.

A Model Context Protocol server for intelligent task management in AI-powered development environments, providing file-based storage, dependency management with cycle detection, and an interactive CLI.

Simplified Trello-style task management via MCP with 11 essential tools for efficient CRUD operations and a real-time web dashboard.

A secure MCP server providing controlled access to pixi tasks and commands, eliminating agent bash circumvention. It exposes 11 pixi tools through 4 meta-tools for ~95% context savings.

Provides a task passport system for handoff across AI harnesses, enabling users to list, open, create, and checkpoint tasks with stable IDs and verified state.

A Model Context Protocol server providing comprehensive task management capabilities with support for project organization, task tracking, and automatic PRD parsing into actionable items.

Enables AI assistants to manage GitHub issues using deterministic priority scoring and concurrency-safe locking. It supports a structured eight-phase workflow from issue selection through pull request review to ensure consistent prioritization and progress tracking.

Enables clients to read files, list tests, and run tests through MCP tool calls, while refusing apply operations.