"A guide for developing WeChat Mini Programs" matching MCP servers:

MCP server that helps AI agents inspect Minecraft project evidence (crash logs, mod files, datapacks) before writing development code.

Enables AI agents to access and manage project guidelines, documentation, and context through a structured content system with template support and workflow management.

A beginner-friendly Model Context Protocol (MCP) server that helps users understand MCP concepts, provides interactive examples, and lists available MCP servers. This server is designed to be a helpful companion for developers working with MCP. Also comes with a huge list of servers you can install.

Enables AI assistants to control WeChat mini-programs running in WeChat Developer Tools through MCP tools. Provides automation capabilities for launching, navigating, querying, and interacting with pages and elements.

Enables AI assistants to automate WeChat Developer Tools for mini programs, allowing navigation, inspection, and manipulation of pages and components through the miniprogram-automator API.

Local-first MCP graph intelligence server providing RRF hybrid search, multi-hop traversal, source snippets, and rationale nodes for AI agents, without Docker or web UI.

Local MCP server for token optimization, providing tools to compress code/JSON, optimize prompts, and manage placeholder-based content redaction and hydration to reduce LLM token usage.

A Chinese-friendly, locally running MCP server for WeChat Mini Program engineering, helping developers break down ideas into actionable tasks, inspect projects, generate blueprints, and perform security scans.

Provides access to clean code guide documents and enables code quality inspection of external project files based on coding standards and best practices.

A procurement scenario MCP server for testing whether pending work can resume after a service restart, comparing legacy and modern continuation. It uses SQLite for data persistence and demonstrates real MCP protocol messages.

Enables OpenAI Codex users to drive coding tasks remotely from their phone chat: sending messages, images, files and voice to Codex, and receiving task-completion notifications with Markdown-formatted results and media. Includes 24-hour window queueing, typing indicators, login/status tools, and watchdog-backed reliability so nothing is silently dropped.

Enables local tool calling over Model Context Protocol via stdio, providing deterministic tools such as calc.add, text.word_count, and text.summarize_naive after JSON-RPC handshake and discovery.

Connects WeChat Mini Program tooling to MCP and automation workflows. Provides scripts for opening, previewing, and uploading projects, as well as automator smoke tests.

Enables AI agents to control WeChat DevTools on Windows through the official CLI and mini program automation SDK, supporting project operations, simulator navigation, element interaction, screenshots, evaluation, and wx API calls.

Enables coding agents to read Jira Cloud issues, search via JQL, and retrieve comments, attachments, and change history through a lightweight, context-efficient MCP toolset.

Enables users to list, select, and continue existing local Codex chats through WorkBuddy's WeChat assistant by sending messages to the same chat ID and reading text replies.

Provides comprehensive design principles and best practices to help LLMs generate modern, accessible web pages through guidance on layouts, colors, and typography. It enables users to review design approaches and access expert recommendations for responsive design, component structure, and current industry trends.

Provides Xcode build, test, and package management operations through the Model Context Protocol.

Agent-First CRUD store MCP server — schema.yaml driven, SQLite backend, multi-table in a single daemon.

Enables dynamic reverse engineering and debugging of WeChat MiniProgram JavaScript through the Chrome DevTools Protocol, letting AI agents enumerate and search scripts, set breakpoints, step through paused frames, trace function calls, hook miniprogram APIs such as wx.request, and capture network requests to analyze encryption, signing, and anti-scraping logic. It also works against Chrome, Node.js, and Electron runtimes, with tools for extracting code bundles and page business logic.

Enables an AI to open a workspace, list files, read and write files within a configured workspace directory, and render an embedded workspace UI inside ChatGPT. File access is restricted to that workspace, with hidden folders and symlinks skipped.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A guide for implementing Model Context Protocol (MCP) servers that provide AI models with external tools like web search, text manipulation, and mathematical operations.

Enables Codex to consult Claude Code for a second opinion through a local stdio MCP server, exposing the ask_claude tool for text-only reviews and recommendations using existing Claude Code authentication. Codex can request findings and tradeoff analysis without allowing Claude to edit files or run commands.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.

Enables AI coding agents to discover and verify current open-source libraries and models using live GitHub activity, PyPI adoption, license checks, and hardware VRAM estimates before generating code.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.