"A server for finding information about context" matching MCP servers:

Automates Cole Medin's context engineering methodology to generate high-quality Product Requirements Prompts (PRPs) by analyzing existing codebases, asking contextual questions, and synthesizing insights.

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 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.

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.

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 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.

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.

Enables AI agents to query SensorTower's APIs for mobile app market intelligence, including download and revenue estimates, store leaderboards, App Store featuring and ASO keywords, reviews, Apple Search Ads, and audience insights across roughly 76 endpoints. It normalises the API's unit, shape, and error quirks so results arrive clean, capped for model context, and with actionable error hints.

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

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.

MCP server for GoalT, a multi-parent value-propagating goal graph. It enables building and querying goal trees, listing priorities, and opening a live dashboard that highlights the active goal during Claude Code sessions.

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.

Enables reading and editing Avo tracking plans through natural language, with skills for designing new plans and working with existing ones.

Enables AI agents to research mobile apps, compare onboarding and paywall flows, explore App Store reviews, and find visual UI references, bringing real screens and market context into their research.

Collect and analyze user feedback from any app via a single API endpoint, with MCP tools for listing, searching, and stats.

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 query live App Store and Google Play data — keyword demand, rank history, top charts, competitor sets, reviews and ratings — across 100+ countries, directly inside a chat instead of a dashboard. Exposes 35 read-only tools covering app search, ASO keyword profiling, ranking trajectories, and worldwide market comparisons through a remote OAuth-authenticated endpoint.

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.

Enables AI agents to read-only access business intelligence in a Revinho workspace, combining Google Analytics 4, Stripe, and optionally Google Search Console to answer questions about changes, performance, revenue, underperformance, and opportunities.

MCP server for managing Tokei pre-launch and waitlist campaigns, wrapping the Tokei v1 REST API. Enables querying pages, stats, leaderboards, signups, and performing write operations like cloning pages and uploading media through natural language.

A User Story Map and Kanban board that a human and an AI coding agent plan together in real time via MCP, with live bidirectional sync and governance enforcement.

A federated MCP server that combines IBM's engineering-ai-hub tools with its own authoring and orchestration tools for IBM ELM, enabling AI hosts to manage requirements, models, and compliance through a single interface.

Enables external agents to inspect and interact with a local single-project workbench via MCP, providing read-only tools for state, audit, resume, readiness, comparison, impact preview, and repair candidates, while proposals are saved for manual confirmation in the workbench.

Enables AI assistants to conduct research, plan projects, generate PRDs, user stories and task lists, scaffold full-stack starter kits, map codebases, curate context, and execute multi-step development workflows.

Enables transforming grounded AI answers into interactive information views such as comparisons, plans, checklists, timelines, and decision views, while preserving a plain-language fallback.

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.

An MCP server that exposes a Proof workspace to MCP clients, enabling tools for reading/writing concepts, managing ideas and projects, running ideation operators, and more, with live sync and headless authentication.

Public MCP server for agent-created, human-friendly, short-lived surveys. Enables agents to ask structured questions and retrieve answers.

This MCP server assists founders in customer discovery by structuring hypotheses, finding interviewees, generating call guides, and synthesizing insights to achieve product-market fit.