"Logging into Servers and Network Devices via SSH" 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 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 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.

MCP server that synthesizes user feedback from multiple sources into actionable insights. Aggregates reviews, support tickets, and survey responses to identify patterns and priorities.

Read Layerdock website feedback in your coding agent. Each pin comes with the CSS selector, screenshot, page URL and the console and network trace captured when the client reported it. Fix the bug, reply on the thread and mark it resolved without leaving the editor. Works with Claude Code, Cursor, Codex CLI, Windsurf, VS Code, Zed and Antigravity.

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.

Enables users to turn ideas or PRDs into component selections and architecture designs, audit existing projects with static scans, and manage long-running planning/auditing tasks with caching, cancellation, budget tracking, and checkpoint resume via MCP tools.

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.

Turns product feedback pinned to a live UI into an actionable backlog for Claude Code — list comments, open one with its target element's HTML, computed styles and screenshot, and update its status.

Enables agents to securely collect and submit user feedback (voices) into VOD, with per-submission confirmation, batch size limits, host-identity sourcing, and declarative guardrails that block database access and credential reads. Also exposes read-only tools for version info, auth self-check, and reviewing locally submitted entries.

Enables AI assistants to search a community-driven technical leadership radar, inspect entries by dimension and sector, assess plans against it, and display an interactive view locally without network access.

Prevents premature AI coding by transforming vague product ideas into structured specifications, architecture decisions, and acceptance criteria through a series of interrogation and compilation tools.

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 AI agents to generate structured PRDs, decompose epics into testable user stories, validate Given/When/Then acceptance criteria, and export markdown backlogs.

MCP server that transforms Voice of Customer data into actionable customer experience insights through structured analysis and synthesis.

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.

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.

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 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.

Enables read-only Jira Data Center insights by default, with opt-in audited write tools, sprint and release health summaries, and structured issue search via MCP.

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

An A/B experiment runner for the A2A network that provides deterministic sticky bucket assignment, conversion recording, and two-proportion Z-test statistical significance calculation, with pay-per-call pricing via x402 on Base USDC.

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

Transforms raw business ideas into complete product strategies by orchestrating a specialized AI team for market research, competitive analysis, persona building, and financial modeling, culminating in a pitch-ready presentation.

Manages and authoring of business rules in a scenario studio tool, enabling agents to read, update, link rules, and assign them to capabilities via MCP tools.

Enables users to transform raw multi-source enterprise findings into complete, structured strategic documents, auto-generating executive summaries, risk registers, decision matrices, and appendix citations. It runs as a zero-dependency Python MCP server that works with Claude Desktop, Cursor, and other MCP-compatible clients.