"Using Linear with team-specific templates for ticket creation" matching MCP servers:

Enables orchestrating a reusable team of expert agents (PM, architecture, development, QA, security) to analyze a project's files and produce consolidated recommendations. It exposes tools to list experts, ask a single expert, or run the full team from MCP clients.

Enables users to plan, coordinate, and govern multi-agent teams using MongoDB for shared context, token budgets, and checkpoint recovery.

Enables structured role-to-role handoffs and merge gating for multi-agent collaboration. It persists evidence and computes approval gates without invoking LLMs.

A server that enables AI assistants to interact with Linear's project management tools through the Model Context Protocol, supporting features like searching, creating, and updating issues, adding comments, and retrieving user profiles and team information.

Enables users to leverage a team of specialized AI agent personas like Business Analysts and Product Managers through a unified interface across multiple LLM providers. It streamlines agile development workflows by providing tools for model discovery, unified prompt delivery, and role-specific decision making.

Enables collaboration between multiple AI models (GPT, Claude, Gemini) to work together on complex tasks, with intelligent task distribution and role-based expert assignment for code development, review, and optimization.

An MCP server that enables Claude to train a linear regression model by simply uploading a CSV file, handling the entire ML pipeline from data preprocessing to model evaluation.

Enables autonomous hierarchical multi-agent orchestration for MCP, with persistent SQLite state, real-time web monitoring, and support for mixing multiple CLI and direct API execution providers.

Autonomous AI software development pipeline that transforms tickets into production-ready code through planning, coding, testing, reviewing, and delivery stages.

An AI-centric MCP server that enables automated Xilinx Vivado workflows, including project management, synthesis, implementation, and timing analysis. It allows AI agents to drive hardware design processes while integrating directly with the official Vivado GUI for visual context.

A Model Context Protocol server that enables role-based context management for AI agents, allowing users to establish specific instructions, maintain partitioned memory, and adapt tone for different agent roles in their system.

Turns Claude Code into a self-driving AI company with autonomous CEO, agent teams, and self-improvement capabilities.

A Model Context Protocol (MCP) server that turns multiple AI coding agents into a coordinated team that chats, debates, remembers, audits security, and works in parallel on the same project.

Enables Claude Code to orchestrate a team of independent Claude Code sessions within iTerm2 for parallel task execution and isolated git worktree management. It provides tools to spawn, monitor, and message worker sessions while maintaining full visibility and control over their terminal windows.

A Model Context Protocol server that exposes multiple AI tools over SSE transport with JWT-based secure authentication, allowing for dynamic tool registration and session management.

A reusable AI software development team built on MCP. 13 specialized agents (Project Manager, Backend, Frontend, QA, Security, DevOps, UX, and more) collaborate via shared SQLite state. Exposes 44 MCP tools across 12 domains. All discussions and decisions are stored in the database so agents get back up to speed immediately when re-loaded.

A local MCP server that lets Hermes supervise Claude Code, delegating focused coding, research, or review tasks to the Claude Code CLI and managing worker sessions, background jobs, cancellations, and read-only reviews.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

Enables AI agents to control the Unity Editor through MCP, allowing scene building, runtime scripting, visual QA, and more.

Enables real-time communication and orchestration of multiple AI agents with a web dashboard for monitoring agent activities, tasks, and artifacts.