How do I find my Face++ API Key and Secret?

Log in to the [Face++ Console](https://console.faceplusplus.com.cn/), go to [Dashboard] -> [API Key], and you will find your unique Key and Secret there. Ensure you have the necessary permissions enabled.

Can I analyze images from a local file?

This server currently supports analysis via `image_url`. To use local files, you should upload them to a public or private storage and provide the resulting URL to the tools.

What attributes can be returned during face detection?

Common attributes include gender, age, emotion, head pose, smile, face quality, and skin status. You can specify these in the `return_attributes` parameter of the `detect_face` tool.

Face++ / Megvii MCP Server for VS Code Copilot 10 tools — connect in under 2 minutes

Name: Face++ / Megvii
Availability: InStock
Author: Vinkius

code.visualstudio.com/docs/copilot/chat/mcp-servers

Built by Vinkius GDPR 10 Tools IDE

GitHub Copilot in VS Code is the most widely adopted AI coding assistant, embedded directly into the world's most popular code editor. With MCP support in Agent mode, Copilot can access external data and APIs to generate context-aware code grounded in real-time information.

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Classic Setup·json

{
  "mcpServers": {
    "face-megvii": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Face++ / Megvii MCP Server

Empower your AI agent to orchestrate your computer vision operations with Face++ (Megvii), the dominant facial recognition platform in China. By connecting Face++ to your agent, you transform complex image analysis and identity verification into a natural conversation. Your agent can instantly detect faces, compare similarities between photos, search within face databases (FaceSets), and analyze human body skeletons or gestures without you ever needing to navigate the comprehensive web console. Whether you are conducting KYC audits or monitoring visual content, your agent acts as a real-time vision intelligence assistant, providing accurate and fast results from a single, unified source.

GitHub Copilot Agent mode brings Face++ / Megvii data directly into your VS Code workflow. With a project-scoped config, the entire team shares access to 10 tools. Copilot queries live data, generates typed code, and writes tests from actual API responses, all without leaving the editor.

What you can do

Face Orchestration — Detect faces in images and retrieve detailed attributes like age, gender, and emotion.
Identity Verification — Compare two images to calculate confidence that they belong to the same person.
FaceSet Management — Create and manage searchable face databases for large-scale matching.
Body & Skeleton Analysis — Detect human bodies and skeletons to analyze posture and movement.
Gesture Recognition — Identify specific hand gestures from image data.

The Face++ / Megvii MCP Server exposes 10 tools through the Vinkius. Connect it to VS Code Copilot in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Face++ / Megvii to VS Code Copilot via MCP

Follow these steps to integrate the Face++ / Megvii MCP Server with VS Code Copilot.

Create MCP config

Create a .vscode/mcp.json file in your project root

Add the server config

Paste the JSON configuration above

Enable Agent mode

Open GitHub Copilot Chat and switch to Agent mode using the dropdown

Start using Face++ / Megvii

Ask Copilot: "Using Face++ / Megvii, help me...". 10 tools available

Why Use VS Code Copilot with the Face++ / Megvii MCP Server

GitHub Copilot for Visual Studio Code provides unique advantages when paired with Face++ / Megvii through the Model Context Protocol.

VS Code is used by over 70% of developers. adding MCP tools to Copilot means your team can leverage external data without leaving their primary editor

Project-scoped MCP configs (`.vscode/mcp.json`) let you commit server configurations to your repository, ensuring the entire team shares the same tool access

Copilot's Agent mode integrates MCP tools seamlessly with file editing, terminal commands, and workspace search in a single agentic loop

GitHub's enterprise compliance and audit features extend to MCP tool usage, providing visibility into how AI interacts with external services

Face++ / Megvii + VS Code Copilot Use Cases

Practical scenarios where VS Code Copilot combined with the Face++ / Megvii MCP Server delivers measurable value.

Live API integration: Copilot can query an MCP server, inspect the response schema, and generate typed API client code in the same step

DevSecOps workflows: security teams can give developers access to domain intelligence tools directly in their editor for real-time vulnerability assessment during code review

Data pipeline development: Copilot fetches sample data via MCP and generates transformation scripts, validators, and test fixtures from actual API responses

Documentation generation: Copilot queries available tools and auto-generates README sections, API reference docs, and usage examples

Face++ / Megvii MCP Tools for VS Code Copilot (10)

These 10 tools become available when you connect Face++ / Megvii to VS Code Copilot via MCP:

add_face_to_faceset

Add faces to a FaceSet

compare_faces

Compare two faces for similarity

create_faceset

Create a new FaceSet

detect_body

Detect human bodies in an image

detect_face

Detect faces in an image

gesture_detect

Detect hand gestures

get_faceset_detail

Get details of a FaceSet

remove_face_from_faceset

Remove faces from a FaceSet

search_face

Search for a face in a FaceSet

skeleton_detect

Detect human skeletons

Example Prompts for Face++ / Megvii in VS Code Copilot

Ready-to-use prompts you can give your VS Code Copilot agent to start working with Face++ / Megvii immediately.

"Detect faces in this image URL: [URL]."

"Compare these two images to see if they are the same person: [URL1] and [URL2]."

"Check for any human body detected in this photo: [URL]."

Troubleshooting Face++ / Megvii MCP Server with VS Code Copilot

Common issues when connecting Face++ / Megvii to VS Code Copilot through the Vinkius, and how to resolve them.

MCP tools not available

Ensure you are in Agent mode in Copilot Chat. MCP tools only appear in Agent mode.

Face++ / Megvii + VS Code Copilot FAQ

Common questions about integrating Face++ / Megvii MCP Server with VS Code Copilot.

Which VS Code version supports MCP?

MCP support requires VS Code 1.99 or later with the GitHub Copilot extension. Ensure both are updated to the latest version. Older versions of Copilot may not expose the Agent mode toggle.

How do I switch to Agent mode?

Open the Copilot Chat panel and look for two mode options: "Ask" and "Agent". Click "Agent" to enable autonomous tool calling. In Ask mode, Copilot provides conversational answers but cannot invoke MCP tools.

Can I restrict which MCP tools Copilot can access?

Yes. VS Code shows a tool consent dialog before any MCP tool is invoked for the first time. You can also configure tool access policies at the organization level through GitHub Copilot settings.

Does MCP work in VS Code Remote or Codespaces?

Yes. MCP servers configured via .vscode/mcp.json work in Remote SSH, WSL, and GitHub Codespaces environments. The MCP connection is established from the remote host, so ensure the server URL is accessible from that environment.