"Metallurgical Engineering and Steel Plant Processing Information" matching MCP servers:

Enables LLMs like Claude to navigate the web through Puppeteer-based tools and Steel. Based on the Web Voyager framework, it provides tools for all the standard web actions click clicking/scrolling/typing/etc and taking screenshots.

An MCP server that gives coding agents structured plant data for garden planning: species care profiles, companion checks that explain themselves, and frost-date planting windows derived from ten years of observed weather.

An MCP server that gives AI clients a Steel-managed Chromium browser to read pages that block plain fetch, take screenshots, and interact with sites via clicking, typing, and form filling, with explicit browser sessions and access to the accessibility tree or markdown.

A local STDIO MCP server that bridges MCP clients to the Codex CLI by sending instructions to a configured workspace, exposing task run, status, and result tools with a read-only sandbox and no remote transport.

MCP server that turns coding workflows into explicit execution graphs (DAG) with deterministic command execution, human-in-the-loop gates, and tamper-proof run history for Claude Code.

An MCP server that wraps the steel-dev API to enable AI agents to visit websites with browser automation, supporting both stateless scraping and stateful interactive sessions.

Enforces team engineering standards across Git, code review, Rails, frontend, deployment, incidents, observability, API design, database, ADRs, and technical debt, with tools for branch name and commit message validation.

Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.

Provides coding agents with a shared, Markdown-based engineering knowledge base to search, capture, create, and update internal conventions, API details, infrastructure configs, and development setup via lightweight MCP tools.

An MCP server that exposes three tools for auditing, scaffolding, and triaging agent intent specs against a unified template, helping prevent intent failures in AI agents.

An MCP server that gives an AI assistant a set of real mechanical-engineering tools. Provides deterministic tools like material properties, beam analysis, unit conversion, and curve fitting for engineering calculations.

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.

Enables processing, validation, optimization, and analysis of 3D models with glTF/GLB support, including format conversion, compression (Meshopt/Draco), texture optimization, and detailed model statistics.

Enables image processing tasks such as resizing, compressing, converting formats, cropping, and extracting metadata directly within IDEs like Cursor via the Model Context Protocol.

An MCP server plugin for Claude Code that analyzes local AI session logs to provide coaching on coding patterns, tool usage, and productivity insights via tools and slash commands.

Enables AI coding environments to enforce engineering governance through MCP tools and resources for init, check, route, and review workflows.

Provides persistent memory and semantic code understanding for AI assistants using MongoDB Atlas Vector Search. Enables intelligent code search, memory management, and pattern detection across codebases with complete semantic context preservation.

Provides AI assistants with structured access to an organization's engineering standards, practices, and processes through searchable knowledge base with CRUD operations and multi-dimensional organization.

Provides structured templates for security questionnaires, RFP responses, and competitive battlecards to help AI agents and sales engineers draft responses efficiently.

A public MCP server demonstrating how an AI agent can retrieve database schemas and manage local OpenAPI contracts via tools for CRUD operations.