"Accessing a browser programmatically to capture snapshots and logs" matching MCP servers:

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 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 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 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.

A Python-based MCP server that enables AI agents to query the Microsoft 365 Roadmap programmatically.

Enforces a marketing pre-flight: plan the campaign with kill criteria, score each offer on an explainable 0-100 rubric, and require every tactic to cite a scored offer plus a success metric before any spend.

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 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 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.

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

Enables AI tools to connect to the Dovetail API for accessing customer insights and research data.

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 accessing and managing Aha! records, including features, requirements, pages, and documents through natural language.

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.

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

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 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.

Connects MCP clients to a hosted experimentation platform so agents can start, pause, stop, and roll back live website A/B tests, inspect Bayesian results, and capture hypotheses.

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 Claude Code to run multi-round grilling sessions in a browser UI, publishing rounds of questions with options and recommendations that users answer with buttons or free text. Supports per-question asides (re-pitch, visual diagram, plain-language explainer), chat notes between rounds, and a polling contract so sessions can stay open without blocking the client.

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.

Enables users and AI agents to collaboratively create and edit live boards of cards, connections, groups, and notes, with changes synced instantly between the browser and agent.

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.

Enables AI orchestrators to manage hierarchical implementation roadmaps with phases, tasks, and plan-change tracking.

Enables AI coding clients to turn code into a linked product specification and run coherence, coverage, and impact checks to surface gaps and contradictions.

Enables AI agents to interact with a B2B OKR management application to view and manage objectives and key results, with Stytch-backed multi-tenant authentication and role-based access control.

Enables keyword search across source-traceable evidence chunks, listing opportunities linked to supporting evidence, and deterministic ROI calculations with model-proposed inputs and TypeScript-computed dollar figures.

Enables AI agents to query Mixpanel event data, funnel conversion rates, and retention cohorts via MCP tools or natural language.