"Understanding HTTP Requests" matching MCP servers:

A Model Context Protocol server for FeaturePulse feedback management, enabling AI assistants to query feature requests, analyze MRR impact, and manage product roadmaps through natural language.

Official MCP server for FeatureJet, enabling agents to read and act on customer feedback boards: list/search posts, file feature requests, and pull top-voted planned items.

Product management copilot that connects Claude to HelpScout support tickets and ProductLift feature requests. Synthesizes customer feedback across sources, scores themes by convergence, and generates prioritized product plans.

A demo MCP server exposing an in-memory todo list via tools (add_task, list_tasks, complete_task), a resource, and a prompt, over both stdio and HTTP transports.

Enables agents to manage Kanban projects and tasks over MCP, including creating and listing projects/tasks, setting prerequisites, moving/archiving/restoring/deleting/reordering tasks, tracking history, and accessing attachments. Actions affecting multiple tasks return confirmation requests before applying changes.

Enables retrieval of App Store and Google Play reviews, ratings summaries, and ASO keyword rankings for any app using its store ID or package name.

A production-ready MCP server enabling AI assistants to interact with Jira projects, issues, sprints, users, attachments, and worklogs via natural language, with support for both local stdio and remote HTTP transports, dual authentication methods, and enterprise-grade security controls.

Enables AI agents to guide users through pretotyping, turning raw ideas into Lean Canvases, testable hypotheses, and small experiments to validate demand before building.

Enables read-only access to Product Hunt data, including launches, post details, comments, topic search, and user profiles, through MCP tools over Streamable HTTP.

Enables AI agents to interact with VoteShip feature requests, voting boards, roadmaps, and changelogs, including public board access without credentials and authenticated project administration with a project secret.

Enables AI agents to collect, retrieve, and manage feedback on static HTML mockups through 9 MCP tools, with support for local or remote data and stdio/HTTP transports.

Enables interaction with a self-hosted PostHog instance through MCP, providing access to PostHog analytics and product data.

MCP server for Open Feedback, enabling AI assistants to submit, list, get, update status of, and analyze product feedback via a local HTTP API and JSONL storage.

MCP server for managing customer feature requests with role-based approvals, elicitation for high-impact changes, and support for notifications, sampling, and progress tracking. Enables employees to review, prioritize, and approve requests without direct database access.

Connect your AI assistant to Featuriq — the product feedback and roadmap tool for SaaS teams. Browse top feature requests, search feedback with natural language, update statuses, notify users when features ship, and manage your roadmap — all from your AI client. Authenticates via OAuth. No manual API key setup needed.

Provides Claude with tools to make Ship/Delay/Kill recommendations on feature requests using product metrics, roadmap, and OKRs.

Enables stdio-based MCP clients to read and write the Propyte Mejoras IA board on hub.propyte.com by translating JSON-RPC stdio messages into authenticated HTTPS requests to the Hub.

MCP server that lets AI assistants create projects, epics, and tasks in the TuDu app through natural conversation. It securely connects over local HTTP with token authentication and requires on-screen confirmation before writing anything.

Inline review comments for markdown specs and design docs. Agents request human review mid-task via MCP and pause until you send feedback.

A Python-based MCP server that enables AI agents to query the Microsoft 365 Roadmap programmatically.