"Fetching data from an MCP server" matching MCP servers:

Enables creating, managing, and analyzing live audience surveys on rifts.to directly from an AI client. Supports creating surveys, listing them, retrieving results, and closing surveys via natural language.

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

Pre-build reality check for AI coding agents. Scans GitHub, Hacker News, npm, PyPI & Product Hunt in parallel — returns a 0-100 reality signal with real competitor data.

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.

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.

MCP server for AI agents providing 300 curated Japanese home & lifestyle products across 31 categories. Features mm-precision dimension search, related-item chains (1 product → 3-5 accessories), shelf+storage coordination, and Rakuten/Amazon affiliate links.

Enables MCP clients to query the IndeCX public API for survey data, including actions, questionnaires, answers, invites, non-respondents, categories, blocklists, and branches.

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.

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

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 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.

An MCP server for the Trello REST API. Exposes ~36 curated tools for boards, lists, cards, checklists, labels, members, and search.

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.

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.

Stop your AI agent from rebuilding what already exists. MCP server that checks GitHub, npm and Python repos for maintained alternatives before you scaffold.

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.