# Codex JetBrains

> Use this tool when you need to integrate AI-powered code generation and completion capabilities with JetBrains IDEs. It solves problems such as streamlining coding tasks, improving code quality, and enhancing developer productivity by providing automated code suggestions and refactoring assistance. The tool takes in natural language inputs and outputs generated code, making it ideal for use cases like coding assistance and automated development within the JetBrains ecosystem.

Canonical page: https://skillsregistry.net/skills/nealzhi-codex-jetbrains  
JSON: https://api.skillsregistry.net/v1/skills/nealzhi-codex-jetbrains

## Description

Codex JetBrains is an MCP server that integrates OpenAI Codex capabilities with JetBrains IDEs. It exposes code generation and completion tools through MCP, allowing AI assistants to interact with JetBrains development environments for tasks like code suggestions, refactoring assistance, and automated code generation within the JetBrains ecosystem.

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/nealzhi-codex-jetbrains)
- **Repository:** <https://github.com/nealzhi/codex-jetbrains-mcp>

## 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": "nealzhi-codex-jetbrains"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nealzhi-codex-jetbrains` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nealzhi-codex-jetbrains/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