"Resources and Information on Mechanical Engineering" matching MCP servers:

Automates Cole Medin's context engineering methodology to generate high-quality Product Requirements Prompts (PRPs) by analyzing existing codebases, asking contextual questions, and synthesizing insights.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

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.

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.

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.

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.

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

Enables traceable requirement discovery, technical alignment, and ISO-aligned process checking through deterministic MCP tools and resources, without requiring an embedded LLM.

Prioritizes tasks by eliminating distractions, returning a ranked shortlist based on a given goal.

Enables agents to create and drive instrumented Design Thinking sessions, inspect the append-only journal, and retrieve dossiers and handoff specs through MCP tools and resources.

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 MCP clients to search and retrieve product management articles, talks, podcasts, related content, live events, and job listings from Mind the Product through read-only tools and resources.

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 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.

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.

Enables AI agents to guide users through pretotyping, turning raw ideas into Lean Canvases, testable hypotheses, and small experiments to validate demand before building.

Headless MCP server for Simpson Strong-Tie product data. Provides AI agents with structural connector lookups, load calculations, code compliance verification, and engineering specifications.

Enables agents to discover and validate SaaS opportunities mined from real user complaints across eight public sources, scoring ideas for commercial intent. Also allows fetching detailed dossiers on specific gaps with source complaints, MVP scope, pricing, competitors, and risks.