"How to create a WeChat Mini Program" matching MCP servers:

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.

A CLI tool that sets up a Model Control Protocol server and deploys it to Cloudflare Workers, allowing you to quickly create custom tools for your Cursor Agent just by writing TypeScript functions.

Scaffold and audit Starter Series projects — MCP server, Claude Code skill, and CLI in one package.

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

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.

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.

An enhanced dynamic MCP server management service that creates, runs, and manages Model Context Protocol servers with multi-language support and strict parameter validation.

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.

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.

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

A minimal MCP server using FastMCP to demonstrate tool creation, including a get_weather example.

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.

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.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

Enables turning requirements documents into RFCs, functional test scenarios, and a traceability matrix, with tools to parse, diff, and verify coverage.

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