内容
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# Claude Inspector
**See what Claude Code actually sends to the API.**
A local MITM proxy that intercepts Claude Code CLI traffic in real-time,
lets you inspect every JSON payload, and analyzes session flows with AI.
[Install](#install) · [Usage](#proxy-mode) · [AI Analysis](#ai-analysis) · [What You'll Learn](#what-youll-learn)
[](LICENSE)
[](https://github.com/kangraemin/claude-inspector/releases/latest)
[](https://github.com/kangraemin/claude-inspector/releases/latest)
**English** | [한국어](README.ko.md)
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---
<p align="center">
<img src="public/screenshots/en-1.png" width="100%" alt="Proxy — Anatomy view" />
</p>
<p align="center">
<img src="public/screenshots/en-2.png" width="100%" alt="Proxy — Request view with cost breakdown" />
</p>
<p align="center">
<img src="public/screenshots/en-3.png" width="100%" alt="Proxy — AI Analysis view" />
</p>
---
## Install
### Homebrew (Recommended)
```bash
brew install --cask kangraemin/tap/claude-inspector && sleep 2 && open -a "Claude Inspector"
```
### Direct Download
Download the `.dmg` from the [Releases](https://github.com/kangraemin/claude-inspector/releases/latest) page.
| Mac (Apple Silicon) | Mac (Intel) |
|---|---|
| [Claude-Inspector-arm64.dmg](https://github.com/kangraemin/claude-inspector/releases/latest) | [Claude-Inspector-x64.dmg](https://github.com/kangraemin/claude-inspector/releases/latest) |
### Upgrade / Uninstall
```bash
# Upgrade
brew update && brew upgrade --cask claude-inspector && sleep 2 && open -a "Claude Inspector"
# Uninstall
brew uninstall --cask claude-inspector
```
---
## Proxy Mode
Intercept **real** Claude Code CLI traffic via a local MITM proxy.
```
Claude Code CLI → Inspector (localhost:9090) → api.anthropic.com
```
**1.** Click **Start Proxy** in the app
**2.** Run Claude Code through the proxy:
```bash
ANTHROPIC_BASE_URL=http://localhost:9090 claude
```
**3.** Every API request/response is captured in real-time.
### 4 Tabs
| Tab | What it shows |
|-----|--------------|
| **AI Analysis** | AI-powered session analysis — flow summary, Mermaid diagram, inline chat |
| **Request** | Full JSON request body, collapsible tree, token/cost breakdown |
| **Response** | Full JSON response with tool_use results |
| **Anatomy** | Detected mechanisms (CLAUDE.md, Skills, MCP, Sub-agents) as colored chips |
---
## AI Analysis
Select captured requests and let Claude (Sonnet) analyze the full session flow.
### What It Produces
- **Step-by-step session summary** — what happened, in what order, with mechanism explanations
- **MCP dynamic loading chain** — how ToolSearch fetches schemas, how deferred tools become callable
- **Skill loading flow** — how slash commands trigger `<command-message>` → Skill `tool_use`
- **Sub-agent patterns** — which requests are main vs sub-agent, and how they relate
- **Mermaid flowchart** — visual diagram of the internal mechanism flow
- **Clickable references** — each step links to the actual Request, scrolling to the relevant `tool_use`
### How to Use
1. Capture some requests via the proxy
2. Click the **AI Analysis** tab
3. Select requests to analyze (click to toggle, Shift+click for range)
4. Click **Analyze Session Flow**
5. Watch real-time streaming as Claude processes the session
6. Click any **Request #N** badge to jump to that request's `tool_use` in the JSON tree
### Inline Chat
After analysis, ask Claude follow-up questions about the session. The chat understands the full analysis context.
### Session Detection
Requests are automatically grouped by session using message content fingerprinting. Different sessions (main conversation, sub-agents, stop hooks) get different colored borders in the sidebar.
---
## What You'll Learn
All discovered from **real captured traffic**. See what Claude Code hides from you.
### 1. CLAUDE.md is injected into every single request
You type `hello`. Claude Code silently prepends **~12KB** before your message:
| Block | What's inside | Size |
|-------|--------------|------|
| `content[0]` | Available skills list | ~2KB |
| `content[1]` | CLAUDE.md + rules + memory | **~10KB** |
| `content[2]` | What you actually typed | few bytes |
**Injection order:** Global CLAUDE.md → Global rules → Project CLAUDE.md → Memory
This ~12KB payload is re-sent with **every request**. A 500-line CLAUDE.md quietly burns tokens on every API call. Keep it lean.
### 2. MCP tools are lazy-loaded — watch `tools[]` grow
Built-in tools (27) ship their full JSON schemas every request. MCP tools start as **names only**.
| Step | What happens | `tools[]` count |
|------|-------------|-----------------|
| Initial request | 27 built-in tools loaded | **27** |
| Model calls `ToolSearch("context7")` | Full schema for 2 MCP tools returned | **29** |
| Model calls `ToolSearch("til")` | 6 more MCP tool schemas added | **35** |
Unused MCP tools never consume tokens. Watch `tools[]` grow as the model discovers what it needs.
### 3. Images are base64-encoded inline
When Claude Code reads a screenshot or image, it's **base64-encoded and embedded directly** in the JSON body:
```json
{
"type": "image",
"source": {
"type": "base64",
"media_type": "image/png",
"data": "iVBORw0KGgo..."
}
}
```
A single screenshot can add **hundreds of KB** to the request payload. Inspector shows you the exact size.
### 4. Skill ≠ Command — completely different injection paths
Typing `/something` triggers one of three completely different mechanisms:
| | Local Command | User Skill | Assistant Skill |
|---|---|---|---|
| **Example** | `/mcp`, `/clear` | `/commit` | `Skill("finish")` |
| **Who triggers** | User | User | Model |
| **Injection** | `<local-command-stdout>` | Full prompt in user msg | `tool_use` → `tool_result` |
| **Model sees** | Result only | Full prompt | Full prompt |
**Commands** run locally and only pass the result. **Skills** inject the entire prompt text — and it **stays in every subsequent request** until the session ends.
### 5. Previous messages pile up — use `/clear` often
Claude Code re-sends the **entire** `messages[]` array with every request:
| Turns | Approx. cumulative transfer |
|-------|---------------------|
| 1 | ~15KB |
| 10 | ~200KB |
| 30 | ~1MB+ |
Most of it is old conversation you no longer need. Running `/clear` resets the context and drops the accumulated weight.
### 6. Sub-agents run in fully isolated contexts
When Claude Code spawns a sub-agent (via the `Agent` tool), it creates a **completely separate API call**:
| | Parent API call | Sub-agent API call |
|---|---|---|
| **`messages[]`** | Full conversation history | Only the task prompt — **no parent history** |
| **CLAUDE.md** | Included | Included (independently) |
| **tools[]** | All loaded tools | Fresh set |
| **Context** | Accumulated | Starts from zero |
Inspector captures both calls side by side, and AI Analysis automatically detects and labels sub-agent sessions.
---
## Development
```bash
git clone https://github.com/kangraemin/claude-inspector.git
cd claude-inspector
npm install
npm start # Dev mode
npm run test:unit # Unit tests
npm run test:e2e # E2E tests (Playwright)
```
## Tech Stack
| Layer | What | Why |
|-------|------|-----|
| **Electron** | Desktop shell, IPC | Native macOS titlebar, code-signed + notarized DMG |
| **Vanilla JS** | Zero frameworks | Entire UI in a single `index.html` — no bundler, no React |
| **Node `http`/`https`** | MITM proxy | Intercepts Claude Code ↔ API traffic, reassembles SSE streams |
| **Mermaid.js** | Flowchart rendering | AI Analysis mechanism diagrams |
| **claude -p** | AI analysis engine | Session flow analysis + inline chat via Claude Sonnet |
> **Privacy**: All proxy traffic stays on `localhost`. AI Analysis runs locally via `claude -p` (your own Claude Code CLI).
## License
MIT
连接信息
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