Google Cloud Translation

AI & Media Processing

Operated by Sourcelane✓ verified

A bulk text translation connector that uses the Google Cloud Translation API to translate lists of strings into 130+ target languages. It produces one translation per input string while preserving input order and providing an index for joins. Key technical features include automatic source-language detection (with optional explicit source), an HTML-safe mode that preserves tags and entities during translation, smart batching to maximize throughput within API request limits, per-row error reporting so failed rows are logged without stopping the run, and character-level metering that reports character counts per input. Outputs conceptually include translated text, detected and target language identifiers, per-item character counts, and per-item success/error status and messages.

Verified Sep 28, 12:10 AM

$0.0001

per 100 characters

Up to 100 per call. Only pay for results returned; failed calls are refunded.

What people use it for

Localize scraped product descriptions for multi-region e-commerce catalogs
Translate support tickets and customer reviews prior to sentiment analysis or summarization
Generate multilingual variants of blog posts, FAQs, and marketing copy for content pipelines
Bulk-localize product titles, descriptions, and attribute values across catalogs
Translate scraped reviews and comments from platforms (e.g., Trustpilot, Amazon, Google Maps, TikTok) into a single working language for analysis

Trust & reliability

7d uptime trend

Window	Uptime	Success rate	p50	p95
24h	—	—	—	—
7d	—	—	—	—
30d	—	—	—	—

Calling contract

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://cool-puffin-608.convex.site/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"google-cloud-translation","params":{"texts":["Hello, world","How are you today?","The quick brown fox jumps over the lazy dog"],"target":"es"},"maxResults":10}'

Request params

Field	Type	Required	Description
`texts`	array	required	List of text strings to translate. Each entry is translated independently.
`target`	string	required	ISO 639-1 language code to translate into (e.g. 'es', 'fr', 'de', 'ja', 'zh-CN'). See https://cloud.google.com/translate/docs/languages.
`source`	string	optional	ISO 639-1 source language code. Leave empty to let Google auto-detect the source language for each text.
`format`	string	optional	How the input texts should be interpreted. Use 'html' to preserve HTML markup during translation.

Each result contains

Field	Type	Description
`index`	integer	Index
`originalText`	string	Original Text
`translatedText`	string	Translated Text
`detectedSourceLanguage`	string	Detected Source Language
`targetLanguage`	string	Target Language
`characterCount`	integer	Character Count
`status`	string	Status
`error`	null	—

Use Google Cloud Translation from Claude, ChatGPT or Cursor

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. Paste one URL.

1Copy your personal connector URL
2In Claude open Settings → Connectors → Add custom connector
3Paste the URL and click Add — done

Manual setup (config files, REST, Python) +

Claude Code

Adds the Sourcelane MCP server with your key as a header.

terminal

claude mcp add --transport http sourcelane https://cool-puffin-608.convex.site/mcp \
  --header "Authorization: Bearer sl_live_your_agent_key"

Claude Desktop (config file)

Alternative to the connector URL: add to claude_desktop_config.json, then restart Claude.

claude_desktop_config.json

{
  "mcpServers": {
    "sourcelane": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://cool-puffin-608.convex.site/mcp",
        "--header",
        "Authorization:${AUTH_HEADER}"
      ],
      "env": {
        "AUTH_HEADER": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

Cursor & Windsurf

Add to ~/.cursor/mcp.json (or Windsurf's mcp_config.json).

mcp.json

{
  "mcpServers": {
    "sourcelane": {
      "url": "https://cool-puffin-608.convex.site/mcp",
      "headers": {
        "Authorization": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

VS Code

Save as .vscode/mcp.json. VS Code prompts for your key once.

.vscode/mcp.json

{
  "servers": {
    "sourcelane": {
      "type": "http",
      "url": "https://cool-puffin-608.convex.site/mcp",
      "headers": {
        "Authorization": "Bearer ${input:sourcelane-key}"
      }
    }
  },
  "inputs": [
    {
      "type": "promptString",
      "id": "sourcelane-key",
      "description": "Sourcelane agent key",
      "password": true
    }
  ]
}

ChatGPT Custom GPT (Actions)

Create a GPT → Actions → Import from URL, then Authentication: API Key, Bearer.

OpenAPI schema URL

https://sourcelane-amber.vercel.app/openapi.json

REST

One POST. Pass maxResults to cap cost.

curl

curl -X POST https://cool-puffin-608.convex.site/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"google-cloud-translation","params":{"texts":["Hello, world","How are you today?","The quick brown fox jumps over the lazy dog"],"target":"es"},"maxResults":10}'

Python, LangChain, CrewAI, OpenAI Agents SDK…

Wrap the REST call as a tool, or point an MCP client at the endpoint.

python

import requests

res = requests.post(
    "https://cool-puffin-608.convex.site/v1/call",
    headers={"Authorization": "Bearer sl_live_your_agent_key"},
    json={
        "listing": "google-cloud-translation",
        "params": {"texts":["Hello, world","How are you today?","The quick brown fox jumps over the lazy dog"],"target":"es"},
        "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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