Operated by Sourcelane✓ verified
Classify, score and flag texts or images — tickets, reviews, leads, product photos — against your own labels, with one typed answer and confidence per row.
A bulk text-and-image classification connector that converts lists of texts and images into structured, typed labels and scores. It applies multiple predefined questions per item in a single pass (supports up to ten questions) and returns, for each input record, one constrained answer per question plus calibrated confidence and per-option probabilities. It supports three question modes—single-choice labels, ordered numeric scores mapped to nearest level labels, and binary yes/no decisions—allowing multi-modal evaluation (text combined with up to four images per record). Outputs include the original text and image references alongside per-item labels, numeric ratings, binary decisions, confidence values, and probability distributions. The connector enforces label-constrained answers (no freeform text) and handles common image formats (JPEG, PNG, WebP, GIF) with automatic resizing; text inputs are evaluated up to an internal length limit.
Verified Sep 28, 3:55 AM
$0.002
per text
Up to 100 per call. Only pay for results returned; failed calls are refunded.
Support ticket triage
Assign messages to the correct team and flag urgent items
Review and comment analysis
Detect sentiment, topics, and whether content is a complaint across many reviews
Lead qualification
Score profiles or form submissions against custom ideal-customer criteria
Content moderation and spam filtering
Flag off-topic, promotional, or abusive text and images with tunable confidence thresholds
Image tagging
Categorize product photos, listing images, or social posts and identify images that violate rules
Cleaning up scraped records
Label or filter scraped rows before ingestion into CRMs or data warehouses
The texts to evaluate — one per line.
Images to evaluate — one URL per line, each evaluated on its own.
When reading from a results, only send these fields to the model, e.g.
When reading from a results, the fields that hold image URLs, e.g.
The questions to ask about every text.
Optional settings
| Window | Uptime | Success rate | p50 | p95 | Calls |
|---|---|---|---|---|---|
| 24h | — | — | — | — | 0 |
| 7d | — | — | — | — | 0 |
| 30d | — | — | — | — | 0 |
Call it through Sourcelane's gateway or MCP server. We run the connector, apply your agent's spend guardrails, and bill only the results returned.
Call it via Sourcelane
curl -X POST https://api.usesourcelane.com/v1/call \
-H "Authorization: Bearer sl_live_your_agent_key" \
-H "Content-Type: application/json" \
-d '{"listing":"bulk-text-classifier","params":{"questions":[{"key":"department","type":"choice","instructions":"Which team should handle this message?","criteria":{"billing":"Payment or subscription issues","technical":"Bugs or integration problems","sales":"Pricing or account questions"}},{"key":"frustration","type":"score","instructions":"How frustrated the customer appears","criteria":["Calm, just stating facts","Frustrated but civil","Very angry, strong language"]},{"key":"is_urgent","type":"noul","instructions":"The message conveys urgency or time-sensitivity"}],"maxItems":5},"maxResults":10}'Request params
| Field | Type | Required | Description |
|---|---|---|---|
texts | array | optional | The texts to evaluate — one per line. Leave empty if you are reading from an existing results instead. |
imageUrls | array | optional | Images to evaluate — one URL per line, each evaluated on its own. JPEG, PNG, WebP and GIF work; large images are resized automatically. |
fields | array | optional | When reading from a results, only send these fields to the model, e.g. 'text' and 'title'. Leave empty to send the whole record. |
imageFields | array | optional | When reading from a results, the fields that hold image URLs (a URL or a list of URLs), e.g. 'displayUrl' or 'images'. Those images are evaluated together with the record's text. |
questions | array | required | The questions to ask about every text. Each question has a 'key' (the output column name), a 'type' ('choice' picks one option, 'score' rates against ordered levels, 'noul' answers yes/no), 'instructions', and 'criteria' (options for choice, ordered levels for score). |
maxItems | integer | optional | Maximum number of texts to evaluate in this run. Set 0 for no limit. Capped at 100 per call. |
concurrency | integer | optional | How many texts to evaluate in parallel. Higher is faster; lower it if you hit rate limits. |
maxImagesPerItem | integer | optional | When a results record has several images, evaluate at most this many of them (1–4). |
Each result contains
| Field | Type | Description |
|---|---|---|
itemIndex | integer | Item Index |
text | string | Text |
is_dog | boolean | — |
is_dog_probability | number | — |
Pick your tool and connect in under a minute. Then just ask — for example: “Transcribe this video and give me timestamps for every product mention: <url>”
Connect Claude
Web, desktop and mobile. One click, then confirm.
Adds the Sourcelane MCP server with your key as a header.
claude mcp add --transport http sourcelane https://api.usesourcelane.com/mcp \
--header "Authorization: Bearer sl_live_your_agent_key"Alternative to the connector URL: add to claude_desktop_config.json, then restart Claude.
{
"mcpServers": {
"sourcelane": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://api.usesourcelane.com/mcp",
"--header",
"Authorization:${AUTH_HEADER}"
],
"env": {
"AUTH_HEADER": "Bearer sl_live_your_agent_key"
}
}
}
}Add to ~/.cursor/mcp.json (or Windsurf's mcp_config.json).
{
"mcpServers": {
"sourcelane": {
"url": "https://api.usesourcelane.com/mcp",
"headers": {
"Authorization": "Bearer sl_live_your_agent_key"
}
}
}
}Save as .vscode/mcp.json. VS Code prompts for your key once.
{
"servers": {
"sourcelane": {
"type": "http",
"url": "https://api.usesourcelane.com/mcp",
"headers": {
"Authorization": "Bearer ${input:sourcelane-key}"
}
}
},
"inputs": [
{
"type": "promptString",
"id": "sourcelane-key",
"description": "Sourcelane agent key",
"password": true
}
]
}Create a GPT → Actions → Import from URL, then Authentication: API Key, Bearer.
https://usesourcelane.com/openapi.jsonOne POST. Pass maxResults to cap cost.
curl -X POST https://api.usesourcelane.com/v1/call \
-H "Authorization: Bearer sl_live_your_agent_key" \
-H "Content-Type: application/json" \
-d '{"listing":"bulk-text-classifier","params":{"questions":[{"key":"department","type":"choice","instructions":"Which team should handle this message?","criteria":{"billing":"Payment or subscription issues","technical":"Bugs or integration problems","sales":"Pricing or account questions"}},{"key":"frustration","type":"score","instructions":"How frustrated the customer appears","criteria":["Calm, just stating facts","Frustrated but civil","Very angry, strong language"]},{"key":"is_urgent","type":"noul","instructions":"The message conveys urgency or time-sensitivity"}],"maxItems":5},"maxResults":10}'Wrap the REST call as a tool, or point an MCP client at the endpoint.
import requests
res = requests.post(
"https://api.usesourcelane.com/v1/call",
headers={"Authorization": "Bearer sl_live_your_agent_key"},
json={
"listing": "bulk-text-classifier",
"params": {"questions":[{"key":"department","type":"choice","instructions":"Which team should handle this message?","criteria":{"billing":"Payment or subscription issues","technical":"Bugs or integration problems","sales":"Pricing or account questions"}},{"key":"frustration","type":"score","instructions":"How frustrated the customer appears","criteria":["Calm, just stating facts","Frustrated but civil","Very angry, strong language"]},{"key":"is_urgent","type":"noul","instructions":"The message conveys urgency or time-sensitivity"}],"maxItems":5},
"maxResults": 10,
},
timeout=300,
)
body = res.json()
print(body["receipt"]["chargedMicros"], "micro-USD for", body["receipt"]["results"], "results")
print(body["data"])—
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