"Screen sharing or remote desktop access software" matching MCP servers:

Enables converting software development requirements into traceable estimates, WBS breakdowns, PERT calculations, risk registers, roadmaps, quotations, and professional PDF proposals or action plans. It supports reviewing assumptions, exclusions, scope gaps, and commercial documentation before sending deliverables to clients.

Provides a local, agent-maintained product context layer over MCP, serving structured strategy, competitor, customer feedback, and feature inventory data to any AI tool such as Claude, Cursor, or ChatGPT, with local data storage, bring-your-own-LLM support, and weekly evidence-based roadmap reviews that can sync suggestions to Jira or Linear.

Turns your AI host into a product videographer — scripted screen recordings of your own web app with a gliding cursor, camera zooms, highlight callouts, captions, and branded transitions, plus marketing-grade screenshots. Automatic dark-frame cleanup and MP4/GIF export. Free, MIT, 100% local — no account, no API keys.

Enables AI assistants to search and retrieve verified software comparisons, including current pricing with source and date, and ranked alternatives for software switching decisions.

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

MCP server for sharing markdown/text as beautiful, permanent web pages via plsreadme, with tools to share files/text, update and delete docs, and list previously shared links.

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.

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 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.

Enables managing software delivery from intake through stabilization via an evidence-gated hierarchical state machine, with tools for transitions, work items, blocking, resuming, and status rendering.

Enables coding agents to generate software engineering documents — PRD, SRS, ERD, SDD, design spec, traceability matrix, and agent instructions — as Markdown so they build from written specifications instead of guessing. Unsupplied inputs are marked [NOT SUPPLIED] or UNMAPPED rather than filled with invented data.

Enables interaction with PostHog analytics platform, allowing users to list projects, create annotations, and search insights through natural language in Claude Desktop.

An MCP server that connects Claude to ProdPad, giving Claude direct access to your product management data including ideas, feedback, roadmaps, OKRs, and initiatives.

Guides product design through mandatory phases—discovery, definition, prioritization, flows, and verification—so an AI assistant can run a project from problem to verified scope, with strict or free progression modes.

Enables goal-driven plan simplification by tracing each step's necessity, detecting cycles, broken links, and transitive waste, and classifying items as required or pointless with review and recheck capabilities.

Enables AI assistants to create and validate surveys, distribute them, read and tag responses, and generate reports or exports through a hosted Streamable HTTP MCP endpoint with API-key authentication.