"Using Google Search to Find Answers" matching MCP servers:

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 reading release lifecycle status, recent written reviews and bulk monthly report CSVs for allowlisted apps, and searching the full pinned Play API catalog with each method's implementation status. Read-only by design, with keyless authentication, explicit app allowlists and bounded, GET-only access to official Google interfaces.

An MCP server that exposes Google Play Console analytics to AI agents, including store-listing acquisitions by traffic source, installs, uninstalls, ratings, crashes, subscriptions, and reviews by reading bulk CSV reports from Cloud Storage.

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.

Enables triaging product feedback over a local dataset, including search, theme clustering, severity tagging, and drafting PRD-ready problem statements.

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

An MCP server that reads a team's interviews, tickets, and docs to build a model of the product, exposing tools to ask questions, list contradictions and gaps, and draft documents, with all answers citing their source fragments.

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.

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 AI assistants to perform structured decision-making using the Analytic Hierarchy Process (AHP), allowing users to define criteria, compare options pairwise, and calculate ranked results with consistency validation.

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.

Enables MCP clients to query the IndeCX public API for survey data, including actions, questionnaires, answers, invites, non-respondents, categories, blocklists, and branches.

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.

Generate production-ready Product Requirement Documents with full AINative platform awareness and persistent memory. Enables AI agents to create, validate, and manage PRDs using ZeroDB for cross-session storage and 18 tools including generation, templates, validation, and semantic search.

Provides adaptive question cards and guided multi-round interviews inside Codex, letting users clarify requirements one decision at a time and automatically sending chosen answers into the conversation.

MCP server that connects to Jira Data Center, enabling issue search, retrieval, creation, comments, workflow transitions, project listing, arbitrary JQL, and turning meeting notes into structured Jira stories, tasks, and bugs.

Enables customer feedback management by integrating with Canny.io, supporting board listing, post retrieval, search, and creation.