"Linear" matching MCP servers:

Enables AI assistants to work with Linear via the Model Context Protocol, covering issue/project management, resource and prompt access, webhooks, and OAuth app setup.

Enables MCP clients to read and manage Linear issues, sub-issues, relations, comments, projects, cycles, teams, users, labels, and workflow states using a personal API key.

Enables agentic co-authoring of feature specs, decomposition into architecture-validated tickets, and idempotent syncing to Linear as projects with epics, sub-issues, and dependencies.

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

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.

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.

Enables an agent to run 20 product-management workflows that convert call notes, specs, customer feedback and competitor changes into deduped Linear issues, PRD drafts, roadmap sheets, digests and weekly project updates. Orchestrates only the tools each workflow needs across Granola, Linear, Slack, Notion, GitHub, Stripe, Firecrawl, Tavily and Google Workspace, using credentials kept in the user's own OS keychain.

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.