"A server for accessing or retrieving data from GitHub" matching MCP servers:

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.

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 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 fetching daily Product Hunt launches as dataset rows with maker names, product website and company domain, X and LinkedIn links, votes, rank, and topics. Users can filter by specific days or days back, topics, keywords, and minimum votes, or skip already-seen launches on a schedule.

It enables solo builders to automatically log product changes to PostHog and later get statistically honest verdicts on whether those changes moved key metrics, without needing enough traffic for A/B tests.

Enables creating, managing, and analyzing live audience surveys on rifts.to directly from an AI client. Supports creating surveys, listing them, retrieving results, and closing surveys via natural language.

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

Pre-build reality check for AI coding agents. Scans GitHub, Hacker News, npm, PyPI & Product Hunt in parallel — returns a 0-100 reality signal with real competitor data.

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.

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.

Enables agents to evaluate whether a product-adoption message is worth sending by applying a fixed, evidence-based rubric to a draft, recipient context, evidence, and the agent's own assessment, returning a send, revise, or hold recommendation with a score and reasons.

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 clients to create AI-powered forms from natural language descriptions, preview, publish, and close them, and then list, summarize, and export collected responses as CSV. It ships nine tools so an agent can run a form end to end.

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

Enables AI assistants to validate drafted user stories against INVEST and acceptance-criteria rules, suggest splits for oversized stories, and export finished backlogs to Markdown, CSV, or Jira CSV.

Deterministic marketing math for AI agents: 62 engines that compute LTV:CAC, CAC payback, pipeline coverage, A/B test significance, budget allocation, pricing and retention from your own numbers. Runs locally with Node 18+, makes no network calls and stores no data.

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

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

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.

Lets AI assistants query a live feedback collection database in plain language, retrieving entry counts broken down by type and classification status, and listing individual submissions filtered by type, urgency, or sentiment. Access is read-only and privacy-preserving, so answers can be produced without exposing submitter email addresses.

Creates synthetic user profiles from research data to validate service designs through natural conversation.

re-backlog idea management with decision tracking, signal aggregation, and RICE scoring. Captures product feedback from Slack, Teams, Discord, and GitHub

Connects Huawei AppGallery Connect operational data to any MCP-capable AI client, letting users analyze report trends across 16 report types, crash and AppFreeze metrics, review and rating insights, and generate Markdown daily or weekly digests. All 13 tools are strictly read-only, run with zero dependencies, and keep credentials in memory only.

Enables a coding agent to keep one JSON feature specification per feature, governed by a progressive schema, and to render it as editable Markdown documents for a product owner. Answers and direct Markdown edits are reconciled back into the validated model through stdio MCP tools, applying coherent changes and reporting those that widen scope or contradict the model.

Enables designing and analyzing retail-offer experiments, including sample-size planning, hash-based cell assignment, lift estimation with CUPED and bootstrap, sample-ratio checks, and experiment lifecycle management. It also supports drafting readouts and accessing synthetic datasets and experiment resources through MCP clients.

Generate SWOT analyses, competitive comparisons, and browse 100+ pre-built industry examples for any company, brand, or topic. Supports 12 languages.

MCP server for IDEA Base — AI-powered project management. Manage projects, tasks, and time tracking directly from Claude Code, Cursor, or any MCP-compatible AI tool.

A hypothesis-driven B2B positioning engine with 8 tools for strategic positioning, competitive analysis, and go-to-market messaging.