Photo Location Finder

AI & Media Processing

Operated by Sourcelane✓ verified

A visual geolocation connector that infers where a photo was taken without relying on EXIF GPS by applying image analysis and landmark recognition to produce structured location metadata: a concise human-readable place name, administrative breakdown (country/region/city), best-guess camera coordinates (latitude/longitude), a categorical confidence score indicating specificity, an array of recognized landmarks, a short textual explanation of the visual cues used (architecture, signage and script, vegetation, license plates, sun angle, etc.), alternative candidate locations with their own coordinates and confidence estimates, and a direct map link to the chosen coordinates. The connector combines scene and landmark detection, text/sign recognition, and contextual visual cues to generate geospatial hypotheses and ranked alternatives for each image.

Verified Sep 28, 3:55 AM

$0.025

per location

Up to 40 per call. Only pay for results returned; failed calls are refunded.

What people use it for

OSINT and journalism: verify where a photo or video frame was taken
Travel content: auto-tag photo libraries with exact locations
Real estate and insurance: confirm a listing or claim photo's location
Stock photo enrichment: fill in missing geographic metadata at scale
Investigative research: pinpoint a scene from background details alone

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://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"image-to-location","params":{"imageFiles":["https://upload.wikimedia.org/wikipedia/commons/thumb/a/a8/Tour_Eiffel_Wikimedia_Commons.jpg/640px-Tour_Eiffel_Wikimedia_Commons.jpg"]},"maxResults":10}'

Request params

Field	Type	Required	Description
`imageFiles`	array	required	Upload up to 10 photos to geolocate. Each photo returns its own results record with location, coordinates, landmarks, and reasoning.

Each result contains

Field	Type	Description
`inputImageUrl`	string	Input Image Url
`locationName`	string	Location Name
`country`	string	Country
`region`	string	Region
`city`	string	City
`latitude`	number	Latitude
`longitude`	number	Longitude
`confidence`	string	Confidence
`landmarks`	array	Landmarks
`reasoning`	string	Reasoning
`alternativeGuesses`	array	—
`googleMapsUrl`	string	Google Maps Url
`status`	string	Status
`error`	null	—

Use Photo Location Finder 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://api.usesourcelane.com/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://api.usesourcelane.com/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://api.usesourcelane.com/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://api.usesourcelane.com/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://usesourcelane.com/openapi.json

REST

One POST. Pass maxResults to cap cost.

curl

curl -X POST https://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"image-to-location","params":{"imageFiles":["https://upload.wikimedia.org/wikipedia/commons/thumb/a/a8/Tour_Eiffel_Wikimedia_Commons.jpg/640px-Tour_Eiffel_Wikimedia_Commons.jpg"]},"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://api.usesourcelane.com/v1/call",
    headers={"Authorization": "Bearer sl_live_your_agent_key"},
    json={
        "listing": "image-to-location",
        "params": {"imageFiles":["https://upload.wikimedia.org/wikipedia/commons/thumb/a/a8/Tour_Eiffel_Wikimedia_Commons.jpg/640px-Tour_Eiffel_Wikimedia_Commons.jpg"]},
        "maxResults": 10,
    },
    timeout=300,
)
body = res.json()
print(body["receipt"]["chargedMicros"], "micro-USD for", body["receipt"]["results"], "results")
print(body["data"])

Reviews

—

0 reviews

Leave a review

Loading reviews…