# DingTalk v2

> Use this tool when you need to integrate AI capabilities into your applications or services with a lightweight and efficient MCP server. It solves problems related to handling MCP requests and responses, offering a streamlined approach for AI assistants to interact with external services. Ideal for prototyping AI-powered tools or building microservices, it provides a simple and high-performance interface for containerized deployment using Docker.

Canonical page: https://skillsregistry.net/skills/wllcnm-dingding0646  
JSON: https://api.skillsregistry.net/v1/skills/wllcnm-dingding0646

## Description

This Python-based MCP server, developed by NangePlus, provides a lightweight and efficient implementation for AI assistants to interact with external services. Built with aiohttp for asynchronous operations, it offers a streamlined approach to handling MCP requests and responses. The server is containerized using Docker for easy deployment and scalability. It focuses on simplicity and performance, making it ideal for developers who need a fast, no-frills MCP server for integrating AI capabilities into their applications or services. This implementation is particularly suited for scenarios requiring quick setup and minimal overhead, such as prototyping AI-powered tools or building microservices that leverage AI assistants.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/wllcnm-dingding0646)
- **Repository:** <https://github.com/wllcnm/dingding_mcp_v2>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "wllcnm-dingding0646"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/wllcnm-dingding0646` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/wllcnm-dingding0646/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt