"How to query data from ServiceNow" matching MCP servers:

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.

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.

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

Monitor keyword mentions across Reddit, Hacker News, X, and Bluesky, and triage AI-scored leads from your agent. Connects to the hosted RedReplier MCP server.

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

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 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.

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.

An AI-native product development pipeline that guides users from idea to shipping with structured research, architecture, build, validation, and traceability using 52 tools across 4 domains.

Competitive intelligence platform with 24 tools. Monitor competitor pricing, content, positioning, tech stacks, and AI visibility — track how ChatGPT, Claude, and Gemini rank your brand.

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.

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.

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.

Enables AI agents to query real-time SaaS pricing tiers, compare developer tools side-by-side, and retrieve recent product changelogs.

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

Enables MCP-compatible assistants to query, analyze, and summarize Playloop playtest data such as sessions, builds, insights, funnels, crashes, feedback, and experiments through typed tools.

MCP server that provides demand-signal scanning tools from GitHub, Hacker News, npm, and PyPI to validate digital-product and dev-tool ideas. Enables agents to query repo signals, trends, and download counts via stdio JSON-RPC.

MCP server for reading public Featurebase feedback boards, enabling agents to query user feedback, posts, comments, and statistics.

Provides access to Product Hunt data via the Product Hunt API v2, enabling queries for posts, collections, users, topics, comments, goals, and maker groups.

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

MCP server for interacting with Shortcut (project management) directly from Claude, enabling viewing, searching, and creating stories, epics, and objectives with safe read-only and create operations.

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.

Enables AI agents to query self-hosted product analytics, investigate changes with evidence and coverage checks, and use optional management tools for saved reports, goals, and keys.

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.