# WpfVisualTreeMcp

> WpfVisualTreeMcp — faze79-wpfvisualtreemcp. Use this tool when you need to inspect and interact with running WPF desktop applications, solving problems such as automated testing, debugging, and automation of .NET desktop apps. It provides inputs such as visual tree and dependency properties, and outputs like screenshots and binding errors, with an interface for actions like click, text input, and live property editing. This tool is ideal for use cases requiring runtime injection and manipulation of WPF apps without modifying the target application.

Canonical page: https://skillsregistry.net/skills/faze79-wpfvisualtreemcp  
JSON: https://api.skillsregistry.net/v1/skills/faze79-wpfvisualtreemcp

## Description

Let AI agents inspect and drive running WPF (.NET desktop) apps: visual tree, dependency properties, data bindings and binding errors, DataContext, screenshots (popups included), plus click, select-item, text input, keyboard shortcuts, live property editing and wait-for — via runtime injection, with no changes to the target app.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/u5t3uz5cah)
- **Repository:** <https://github.com/faze79/WPFVisualTreeMcp>

## 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": "faze79-wpfvisualtreemcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/faze79-wpfvisualtreemcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/faze79-wpfvisualtreemcp/pull`

---
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