"Information about Test-Driven Development (TDD)" matching MCP servers:

Validates startup ideas with a deterministic scorecard, evidence brief, and verdict before code is written, integrating with MCP-aware build agents to avoid building dead-on-arrival products.

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.

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.

Enables users to stress-test decisions and plans with structured contrarian analysis, surfacing blind spots, hidden assumptions, and failure scenarios through multiple modes such as counter, probe, redteam, and premortem.

Enables users to conduct evidence-driven product research through MCP by importing documents, extracting JavaScript code clues, recording cited facts and inferences, tracking validation, managing research lifecycles, and exporting Markdown or JSON reports. It provides 25 MCP tools for turning source materials into traceable research findings and verification plans.

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

Enables converting software development requirements into traceable estimates, WBS breakdowns, PERT calculations, risk registers, roadmaps, quotations, and professional PDF proposals or action plans. It supports reviewing assumptions, exclusions, scope gaps, and commercial documentation before sending deliverables to clients.

Enables goal-driven plan simplification by tracing each step's necessity, detecting cycles, broken links, and transitive waste, and classifying items as required or pointless with review and recheck capabilities.

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.

Enables AI assistants to conduct research, plan projects, generate PRDs, user stories and task lists, scaffold full-stack starter kits, map codebases, curate context, and execute multi-step development workflows.

Enables transforming grounded AI answers into interactive information views such as comparisons, plans, checklists, timelines, and decision views, while preserving a plain-language fallback.

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.

Connects an AI assistant to a dealer account so it can build and link a shop website that shows live vehicle stock and takes enquiries and test-drive bookings with no database to run. It also lets the assistant read and change listings, prices, test drives, reviews and leads in plain language, with read-only access by default and every change written to an audit log.

Enables AI assistants to perform software development tasks such as codebase analysis, research, planning, requirements and user-story generation, task management, project scaffolding, and multi-step workflow execution. It integrates with MCP-compatible clients like Claude Desktop, Cursor, and Cline AI.

A Model Context Protocol (MCP) server for Canny feedback management. Enables managing customer feedback, prioritizing features, and streamlining product development through natural language.

Enables Claude Code to query a trained sentiment model and Amazon Electronics review analytics through typed, read-only tools. Supports sentiment classification, statistics, keyword and similar-review search, product summaries and comparisons, negative aspect analysis, and model information.

Enables consumers, developers, and innovators to browse and filter a catalog of credit, wealth, insurance, and treasury product types, enroll in products, build and publish apps, and create, test, and publish new products through role-scoped tools.

It equips AI assistants with specialized software development tools for research, planning, requirements generation, user story creation, project scaffolding, codebase analysis, context curation, task management, and multi-step workflow execution.

Enables AI assistants to research topics, map and analyze codebases, curate development context, and generate product requirement documents, user stories, task lists, fullstack starter kits, and multi-step workflows. It runs as an MCP server over stdio or SSE, or as a CLI/REPL interface for natural-language software development tasks.