> For the complete documentation index, see [llms.txt](https://docs.convai.com/api-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.convai.com/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant.md).

# AI coding assistant

Connect a supported coding agent to the Unreal Editor so it can set up Convai characters and read Convai's skill library for you.

The Convai Unreal Engine plugin registers the Convai Toolset with the engine's own Model Context Protocol (MCP) plugin, adding seven Convai-specific editor actions and a library of Convai skill documents that a connected coding agent can read and call. Use this section once the Convai plugin is installed and you want a coding agent such as Claude Code or Cursor to set up Convai characters, players, and actions inside your Unreal project instead of you wiring them by hand.

{% hint style="info" %}
**Before you begin:** AI coding support requires **Unreal Engine 5.8 or later** and only exists in **Editor** builds — the `ConvaiToolset` module throws a build error on any non-Editor target. On UE 5.0–5.7 the plugin still compiles, but the AI coding tooling is not present. See [AI coding assistant quick start](/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant/quick-start.md) for the full setup walkthrough.
{% endhint %}

### What the Convai Toolset adds

The engine's `ModelContextProtocol` plugin already gives a connected coding agent generic MCP tools for editing a project. The Convai Toolset adds seven AI-callable editor actions on top of that — `SetupConvaiCharacter`, `SetupConvaiPlayer`, `SetupConvaiPawnMovement`, `AddNavMeshVolumeForCurrentLevel`, `SetBlueprintPropertyAndPropagate`, `AddConvaiAction`, and `CreateConvaiActionHandler` — registered with the engine's `ToolsetRegistry` plugin. See [Convai Toolset reference](/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant/convai-toolset-reference.md) for what each action does and its parameters.

The plugin also ships 17 skill documents under `Content/Skills/` in the plugin's own content, which an agent lists and reads through the toolset's `AgentSkillToolset` (`ListSkills` and `GetSkills`). These documents describe Convai workflows such as project setup, MetaHuman setup, actions, and dynamic context, so an agent can look up how a feature works before calling a toolset action. See [Convai AgentSkills](/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant/convai-agent-skills.md) for the full list.

### Supported coding agents

Setup supports five agents: `Claude Code`, `Cursor`, `VS Code`, `Gemini`, and `Codex`. Each agent gets its own project-root context file — for example `CLAUDE.md` for Claude Code — with a sentinel-delimited Convai primer block when you choose to add one. See [Supported coding agents](/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant/supported-coding-agents.md) for the exact file and per-agent behavior.

### Connect a coding agent to your project

Open the Convai editor window, click the **Settings** icon, and select **Set Up AI Coding (MCP)**. Choose an agent, set the setup options, and restart the editor when prompted. See [AI coding assistant quick start](/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant/quick-start.md) for the full walkthrough and verification steps.

### Not the same as a character's own MCP connections

This section covers a coding agent calling Convai's editor tools while you build a project in the Unreal Editor. It is a different subject from [MCP Servers](/api-docs/convai-playground/character-customization/mcp-servers.md), which covers a Convai character calling an external MCP server during a live conversation with a player.

### AI coding assistant pages

<table data-view="cards"><thead><tr><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>AI coding assistant quick start</strong><br>Open Set Up AI Coding (MCP), pick an agent, and verify the setup end to end.</td><td><a href="/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant/quick-start.md">AI coding assistant quick start</a></td></tr><tr><td><strong>Supported coding agents</strong><br>Find the context file, terminal support, and agent-specific options for each of the five supported agents.</td><td><a href="/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant/supported-coding-agents.md">Supported coding agents</a></td></tr><tr><td><strong>Convai Toolset reference</strong><br>Reference for the seven AI-callable editor actions and their parameters.</td><td><a href="/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant/convai-toolset-reference.md">Convai Toolset reference</a></td></tr><tr><td><strong>Convai AgentSkills</strong><br>Reference for the 17 shipped skill documents and how an agent lists and reads them.</td><td><a href="/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant/convai-agent-skills.md">Convai AgentSkills</a></td></tr></tbody></table>


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.convai.com/api-docs/plugins-and-integrations/convai-unreal-engine-plugin/ai-coding-assistant.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.