"A calculator for multiplying two numbers" matching MCP servers:

Calculates ROI, break-even, and cost projections for AI agents and automation projects, providing instant answers without external APIs.

This server assists with A/B testing by calculating required sample sizes and necessary test durations. It provides a suite of significance tests, including z-test, chi-square, and Fisher exact methods, while evaluating the risks of premature peeking.

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.

It enables solo builders to automatically log product changes to PostHog and later get statistically honest verdicts on whether those changes moved key metrics, without needing enough traffic for A/B tests.

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.

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 AI agents to research Amazon reviews and voice-of-customer signals through read-only tools for paginated reviews, complaint evidence, rating summaries, media filtering, and side-by-side comparisons of two products.

A hypothesis-driven B2B positioning engine with 8 tools for strategic positioning, competitive analysis, and go-to-market messaging.

MCP server for GoalT, a multi-parent value-propagating goal graph. It enables building and querying goal trees, listing priorities, and opening a live dashboard that highlights the active goal during Claude Code sessions.

Official MCP server for FeatureJet, enabling agents to read and act on customer feedback boards: list/search posts, file feature requests, and pull top-voted planned items.

Enables reading and editing Avo tracking plans through natural language, with skills for designing new plans and working with existing ones.

Collect and analyze user feedback from any app via a single API endpoint, with MCP tools for listing, searching, and stats.

Enables AI assistants to query live App Store and Google Play data — keyword demand, rank history, top charts, competitor sets, reviews and ratings — across 100+ countries, directly inside a chat instead of a dashboard. Exposes 35 read-only tools covering app search, ASO keyword profiling, ranking trajectories, and worldwide market comparisons through a remote OAuth-authenticated endpoint.

Enables AI agents to read-only access business intelligence in a Revinho workspace, combining Google Analytics 4, Stripe, and optionally Google Search Console to answer questions about changes, performance, revenue, underperformance, and opportunities.

Provides free, zero-marginal-cost MCP tools for structured small business teardown, competitor analysis, review intelligence, and market opportunity scanning, returning research methodology for AI models to execute.

MCP server for managing Tokei pre-launch and waitlist campaigns, wrapping the Tokei v1 REST API. Enables querying pages, stats, leaderboards, signups, and performing write operations like cloning pages and uploading media through natural language.

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.

A federated MCP server that combines IBM's engineering-ai-hub tools with its own authoring and orchestration tools for IBM ELM, enabling AI hosts to manage requirements, models, and compliance through a single interface.

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 group food ordering by interpreting group messages and private budgets, matching requests to menu items, and computing an exact optimized order across at most two restaurants while enforcing per-person spending limits and minimum-order rules.

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.

An MCP server that exposes a Proof workspace to MCP clients, enabling tools for reading/writing concepts, managing ideas and projects, running ideation operators, and more, with live sync and headless authentication.

Public MCP server for agent-created, human-friendly, short-lived surveys. Enables agents to ask structured questions and retrieve answers.

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.

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.

Enables retrieval of App Store and Google Play reviews, ratings summaries, and ASO keyword rankings for any app using its store ID or package name.

A task-management MCP server that enforces strict gates on task states, WIP limits, and closing reasons, refusing operations that would leave the list ambiguous or rotting.

MCP server for noise-reduced X (Twitter) search planning and Feedback-to-Fix engineering handoffs. Enables AI agents to generate structured search plans, filter signals, and build handoff packages via MCP tools.

A production-ready MCP server enabling AI assistants to interact with Jira projects, issues, sprints, users, attachments, and worklogs via natural language, with support for both local stdio and remote HTTP transports, dual authentication methods, and enterprise-grade security controls.

Enables AI agents to run a full QFD session over the Model Context Protocol: build and edit a House of Quality (stakeholder needs, measurable characteristics, relationship cells, trade-off roof, work items), validate it, and read back priorities, gates, the diagonal build order and item progress. It also exports the house as TSV, CSV, JSON, SVG or an Excel workbook, with optional file persistence so a person can keep editing where the agent left off.