"Information about Zen philosophy or practices" matching MCP servers:

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

Provides structured DevOps practices and templates (tracking, documentation, runbooks) to streamline AI-assisted PoC development, reducing CLAUDE.md bloat and ensuring consistency across projects.

Unofficial MCP server for Zen Browser DevTools, enabling AI assistants to inspect and control Zen via Gecko/WebDriver BiDi

Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.

An enhanced Model Context Protocol server that enables Claude to seamlessly collaborate with multiple AI models (Gemini, OpenAI, local models) for code analysis and development tasks, maintaining context across conversations.

A Model Context Protocol (MCP) server for producing better Terraform through CLI analysis (tflint, checkov, trivy, kics, infracost), best-practice guidance from terraform-best-practices.com, cloud provider recommendations (Azure, AWS, GCP), and Terraform Registry resource and module guidance.

Orchestrates multiple AI models (Gemini, OpenAI, Claude, local models) within a single conversation context, enabling collaborative workflows like multi-model code reviews, consensus building, and CLI-to-CLI bridging for specialized tasks.

Gives Claude Desktop access to multiple AI models (Gemini, OpenAI, OpenRouter, Ollama) for enhanced development capabilities including extended reasoning, collaborative development, code review, debugging, and large context analysis with conversation threading.

Provides Python and FastAPI coding best practices with searchable guidelines, code review capabilities, and actionable improvement suggestions with examples across general coding, performance, and code quality categories.

Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

AI-powered Odoo engineering platform providing static analysis, domain knowledge, and 14 MCP tools for code review, model exploration, and security auditing of Odoo modules.

Enables a bot to inspect, query, create, edit, and script Roblox Studio instances in token-cheap batches, plus run Luau, playtests, screenshots, and inputs through Roblox's official Studio MCP connection. It runs locally over stdio or an authenticated local HTTP endpoint, returning small structured answers instead of dumping whole games into context.

MCP server: is this GitHub repo still maintained? A verdict.

Enables querying OpenCode Go subscription quota (rolling, weekly, and monthly usage) and Zen prepaid balance as MCP tools.

Enables AI agents to autonomously manage and improve execution processes for repetitive task types by storing reusable task contexts with associated artifacts (practices, rules, prompts, learnings) and providing full-text search across historical best practices.

Enables AI assistants to search, compare, and get detailed information about MCP servers from the mcpcatalogs.com directory.

Enables AI coding assistants to manage Unleash feature flags, including creation, detection, evaluation, and best practices.

MCP-NixOS is a Model Context Protocol server that provides real-time, accurate information about NixOS packages, options, Home Manager, and nix-darwin configurations, preventing AI assistants from hallucinating about NixOS resources and enabling them to deliver factual system configuration guidance.