"Overview of HTTP (HyperText Transfer Protocol)" matching MCP servers:

Enables AI assistants to identify and quantify value leaks in organizations using Melt's methodology, providing structured estimates instead of generic vendor lists.

Feedback collection for AI agents. Create surveys from JSON schema, collect responses from groups of people, and retrieve structured results.

Enables natural language control of OmniPlan 4 on macOS, allowing creation and manipulation of tasks, resources, dependencies, and project metadata through MCP-compatible agents.

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.

Prevents premature AI coding by transforming vague product ideas into structured specifications, architecture decisions, and acceptance criteria through a series of interrogation and compilation tools.

Model Context Protocol server that enables AI assistants to query and analyze project feedback and bug reports from FeedbackBasket projects, with filtering by category, status, sentiment, and search capabilities.

A Model Context Protocol (MCP) server that connects Trello to Claude Code. Manage your boards, lists, cards, checklists, and more — all through natural language.

Enables management of Azure DevOps work items including Epics, Features, User Stories, Tasks, and Bugs through natural language. Supports CRUD operations, WIQL queries, work item relationships, and retrieval of project metadata such as iterations and area paths.

MCP server that transforms Voice of Customer data into actionable customer experience insights through structured analysis and synthesis.

Enables AI assistants to query and segment event data from Amplitude Analytics via the MCP protocol.

Connects AI agents to the Outset research platform for creating studies, managing recruitment, and querying results via the Model Context Protocol.

Enables AI assistants to search Sunex's lens and imager catalog using natural language queries. It provides tools for finding compatible lenses, sensor specifications, and product details through a public Model Context Protocol server.

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.

Manages and authoring of business rules in a scenario studio tool, enabling agents to read, update, link rules, and assign them to capabilities via MCP tools.

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.

A single source of truth for a product's state, roadmap, and deferred work, read and written equally by you and your AI agent via web dashboard and MCP.

A Model Context Protocol (MCP) server for Canny feedback management. Enables managing customer feedback, prioritizing features, and streamlining product development through natural language.

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 management of PMO entities such as actions, risks, issues, projects, deliverables, decisions, KPIs, and objectives through natural language from any MCP-compatible agent.

Enables conversion of business briefs or authenticated saved projects into structured handoffs for the Lovable plugin, with both anonymous basic mode and authenticated full mode including knowledge base, SEO, WCAG, security, and roadmap guidance.