"Resources or Tools for Performing Data Analysis Tasks" matching MCP servers:

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

Generate SWOT analyses, competitive comparisons, and browse 100+ pre-built industry examples for any company, brand, or topic. Supports 12 languages.

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 conversion of business briefs or authenticated saved projects into structured handoffs for the Lovable plugin, with both anonymous basic mode and authenticated full mode including knowledge base, SEO, WCAG, security, and roadmap guidance.

Remote MCP server for AI-powered competitor intelligence, enabling real-time analysis of any product URL through tools like analyze_competitor and report retrieval.

MCP server that exposes project status tools (plan, milestones, RAID items, blockers) allowing AI assistants to retrieve and analyze project information via natural language.

Query PainSpotter to discover validated business opportunities and trending pain points mined from Reddit, Hacker News, and Product Hunt.

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.

Enables AI assistants such as Claude, Cursor, and Codex to pull structured, source-backed, dated competitive intelligence — positioning, pricing, ads, social, reviews, hiring, momentum, and exploitable weaknesses — for any company in the universe, alongside the user's own projects, reports, battlecards, timelines, and evidence. Read-only by default, with optional opt-in competitor creation and plan-gated tools for deeper analysis.

A Model Context Protocol server that provides Monte Carlo forecasting tools for project duration, cost, completion dates, and sensitivity analysis using three-point estimates and historical throughput.

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.

A local MCP server that gives AI agents read access to Roblox experience analytics via the Open Cloud API, exposing 168 metrics and analysis tools for retention, engagement, monetization, and more.

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.

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.

A Jira-lite MCP server that enables planning-first workflows for AI-assisted development. It manages tickets as markdown files with YAML frontmatter, guiding agents through epics, stories, tasks, and architecture decision records.

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.

8 strategic GTM execution tools for founders, CMOs, and strategy leaders covering PMF assessment, launch planning, customer research, retention, partner programs, crisis management, and competitive intelligence.

Enables AI assistants to validate drafted user stories against INVEST and acceptance-criteria rules, suggest splits for oversized stories, and export finished backlogs to Markdown, CSV, or Jira CSV.

Enables natural language control of OmniPlan 4 on macOS, allowing creation and manipulation of tasks, resources, dependencies, and project metadata through MCP-compatible agents.

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.