"linear" matching MCP servers:

Enables agile sprint backlog velocity calculation and milestone completion prediction through the Model Context Protocol, integrating with MCP-compliant clients for deterministic, low-latency forecasting.

Enables agile sprint backlog velocity calculation and milestone completion prediction for Linear, integrating with MCP-compatible clients through a zero-dependency Python server.

A Python MCP server that gives Claude access to PM workflow data such as sprints, roadmap, blockers, and workload, using synthetic fixture data (no API keys required) and can be forked for real Linear/Jira integration.

Integrates AI assistants with product management tools like Linear and Slack, providing specialized agents for discovery, strategy, prioritization, roadmap planning, and metrics definition via the Model Context Protocol.

Provides a local, agent-maintained product context layer over MCP, serving structured strategy, competitor, customer feedback, and feature inventory data to any AI tool such as Claude, Cursor, or ChatGPT, with local data storage, bring-your-own-LLM support, and weekly evidence-based roadmap reviews that can sync suggestions to Jira or Linear.