Gasoline captures HTTP request and response bodies, letting AI assistants see the actual data flowing between your app and APIs.
The Problem
API debugging with AI assistants is painful. You see a 400 error, but without the response body your AI is guessing. You have to open DevTools, find the request, copy the response, paste it into chat — and repeat for every API issue.
With network body capture, your AI reads the payloads directly.
What Gets Captured
For every network request, Gasoline records:
| Field | Description |
|---|---|
| Request body | POST/PUT/PATCH payloads (up to 8KB) |
| Response body | Server responses (up to 16KB) |
| Headers | Request and response headers (auth stripped) |
| Status code | 200, 401, 500, etc. |
| Content type | JSON, HTML, text, etc. |
| Duration | Request timing in milliseconds |
Filtering
Your AI can query exactly the requests it needs:
// Find failed auth requests
{
"url": "/api/auth",
"status_min": 400,
"status_max": 499
}
// Find slow POST requests
{
"method": "POST",
"limit": 5
}
// Find requests to a specific endpoint
{
"url": "users/profile"
}
MCP Tool: get_network_bodies
| Parameter | Description |
|---|---|
url |
Filter by URL substring |
method |
Filter by HTTP method (GET, POST, etc.) |
status_min |
Minimum status code |
status_max |
Maximum status code |
limit |
Max entries to return (default: 20) |
Example Response
{
"url": "https://api.example.com/users",
"method": "POST",
"status": 422,
"contentType": "application/json",
"duration": 145,
"requestBody": "{\"email\":\"invalid\",\"name\":\"\"}",
"responseBody": "{\"errors\":{\"email\":\"invalid format\",\"name\":\"required\"}}"
}
Your AI immediately sees the validation errors without you lifting a finger.
Size Limits & Safety
| Limit | Value |
|---|---|
| Request body cap | 8KB (larger payloads truncated) |
| Response body cap | 16KB |
| Buffer size | 100 recent requests |
| Total memory budget | 8MB |
| Auth headers | Always stripped |
Privacy
- Auth headers stripped — tokens never appear in logs
- Localhost only — captured data stays on your machine
- Bounded buffers — old requests evicted, never unbounded growth
Use Cases
API Validation Errors
“My form submission is failing.”
Your AI sees the exact validation errors in the response body and can fix the request payload.
Authentication Issues
“I’m getting 401s.”
Your AI inspects the request to see what’s missing and the response for error details.
Data Format Mismatches
“The API returns data but the UI is empty.”
Your AI compares the response structure to what your code expects — spotting field name changes, missing properties, or type mismatches.
Debugging Third-Party APIs
“The Stripe webhook isn’t working.”
Your AI sees both what Stripe sent and how your server responded, identifying the disconnect.