Documentation

Install Ansight Studio, configure your stdio-backed MCP client, integrate the SDK, pair devices, and expose Ansight safely in development builds.

Start with the path that matches the job in front of you. Most teams begin with Ansight Studio setup, connect their AI client through the local bridge, then wire the SDK into a development build.

Choose Your Path

Getting Started

First desktop-to-device setup

Install Ansight Studio, point your agent at the local stdio bridge, add NuGet packages, and pair a device.

MCP Configuration

Configure your AI client

Connect Codex, Cursor, Claude Code, and IDE tooling to the local Ansight Studio stdio bridge.

Ansight Studio

Desktop workflow and MCP tools

Capture and review sessions in Ansight Studio, then open the MCP Tools section for the agent-facing tool reference.

SDK

Runtime integration and tool suites

See the currently available SDKs, then drill into the .NET package, pairing flows, configuration, and remote tools.

Security

Development-only best practices

Keep Ansight local, constrain tool exposure, manage pairing configs intentionally, and avoid shipping the SDK publicly.

Skills

Browse published skill URLs

Open the `/skills` tree, drill into `/skills/dotnet`, and copy the direct markdown URL you want to hand to an agent.
  1. Get Ansight Studio running locally.
  2. Configure your MCP client, preferring the stdio bridge.
  3. Wire your app to the SDK.
  4. Issue a pairing config and connect a device.
  5. Add tool suites only for the development workflows you actually need.
  6. Keep the whole setup out of public release builds.

Available Today

  • The detailed integration docs in this tree currently cover the .NET SDK.
  • The desktop Ansight Studio app hosts the local stdio-backed MCP bridge and pairing workflow.
  • Published prompt skills are indexed at /skills, with the current .NET subtree at /skills/dotnet.
  • Other SDKs are planned, but the .NET package is the only one documented here in depth right now.