"Using Azure DevOps for Task Queries and Code Reviews" matching MCP servers:

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.

Enables managing Azure DevOps work items such as PBIs, tasks, and bugs, along with their comments, directly from MCP-compatible clients like Claude Desktop or Cursor.

Enables AI agents to research Amazon reviews and voice-of-customer signals through read-only tools for paginated reviews, complaint evidence, rating summaries, media filtering, and side-by-side comparisons of two products.

Enables AI assistants and developers to read, filter, compare, and summarize software reviews from G2, Capterra, TrustRadius, and Gartner Peer Insights through a hosted, read-only MCP connection with no review-site login or API keys.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables agents to fetch app reviews from Apple's App Store and Google Play per country store, newest first, filtered by date or star rating, with each scheduled run returning only reviews not seen before. It also returns a per-app, per-country rating trend row with the current rating, rating count, change since the last run, and the star split of new reviews.

Enables discovery of a company's public feature board (Canny, Featurebase, Frill, UserVoice, Productboard) from its domain and retrieval of its most-voted requests with votes, status, comments, and the integrations customers ask for. Supports monitoring runs that surface only new requests, status changes, and vote jumps since a prior run using a saved state key.

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.

Gives AI agents live access to Apple App Store reviews: search the App Store, pull customer reviews for any iOS app, and turn them into insights like rating distribution, average rating per version, top complaint keywords, representative quotes, and side-by-side competitor comparisons.

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

MCP server that synthesizes user feedback from multiple sources into actionable insights. Aggregates reviews, support tickets, and survey responses to identify patterns and priorities.

StorePilot is an MCP server that unifies app portfolio management across Google Play and App Store Connect, with tools for installs, earnings, reviews, cross-store parity, and gated releases.

A Model Context Protocol server that provides Monte Carlo forecasting tools for project duration, cost, completion dates, and sensitivity analysis using three-point estimates and historical throughput.

An MCP server for accelerator programs to query, review, and manage startup applications via natural language. It enables searching applications by sector or impact score, fetching full application details with reviewer notes, listing pending reviews, and flagging applications for panel discussion.

Provides access to Upvote.club public API via stdio, enabling task creation, status checking, platform listing, and API reference queries.

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

Enables read-only queries across App Store Connect and Google Play from one toolset, letting users list apps, track release states, and review merged store feedback without extra dependencies or credentials in demo mode.

Enables AI assistants such as Claude, Cursor, and Codex to pull structured, source-backed, dated competitive intelligence — positioning, pricing, ads, social, reviews, hiring, momentum, and exploitable weaknesses — for any company in the universe, alongside the user's own projects, reports, battlecards, timelines, and evidence. Read-only by default, with optional opt-in competitor creation and plan-gated tools for deeper analysis.

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.

Validates startup ideas with a deterministic scorecard, evidence brief, and verdict before code is written, integrating with MCP-aware build agents to avoid building dead-on-arrival products.

Enables AI assistants to search new software launches, read product pages, find alternatives, and follow daily rankings from inside a chat using public read-only data.

An MCP server for Capacities API 2.0 that enables AI agents to discover, create, read, update, and delete objects, blocks, and daily notes with structured JSON or Markdown, using personal API tokens.

An AI-native product development pipeline that guides users from idea to shipping with structured research, architecture, build, validation, and traceability using 52 tools across 4 domains.

Provides market-intelligence tools for researching AI employee opportunities across Egypt, Saudi Arabia, and UAE using Meta ads evidence, with capabilities for competitor analysis, comparison, and evidence retrieval.

MCP server for Tracetify — trace how any product actually grew, without leaving Claude Code or Cursor.

Turns product feedback pinned to a live UI into an actionable backlog for Claude Code — list comments, open one with its target element's HTML, computed styles and screenshot, and update its status.

MCP server that enables structured decision-making using weighted decision matrices, sensitivity analysis, and robust recommendations.

Lets an AI agent read a Pyxis dashboard's analytics — overviews, funnels, devices, acquisition, backend requests, visits and project settings — using a read-only access token created by an admin and revocable at any time. It runs locally over stdio, holds no state, and exposes only GET-style reads of the live Pyxis API.

Wildberries product analytics by article number with no account or API token: price, discount, rating, reviews, stock, delivery time, price history and competitor comparison. Optional seller tools via the official WB API (sales, orders, stocks, replies to reviews and questions).

Mines public App Store and Steam reviews to surface the complaints, rating drops per version, and common pain points across one app or a set of competitors, with no API keys required. Enables natural-language comparison of up to eight apps or games by country and category so users can spot product opportunities and gaps.