Extract Photo EXIF Metadata
Read embedded EXIF data from photos — GPS coordinates, camera settings, date and time — for location verification and photography analysis.
Identify Photo Shoot Locations
Find where a photo was taken using visual AI analysis — useful for travel recreation, content research, and location scouting.
Quick answer: Use the Photo Location Finder tool through ToolRouter to identify photo shoot locations directly from Claude, ChatGPT, Microsoft Copilot, and OpenClaw — connect once, then drive it with plain-language prompts. No code required.
ToolTravel photos, editorial shoots, and viral images often feature locations people desperately want to visit — but the exact spot is never mentioned. Finding it means reverse image searching, combing through comment threads, or asking on Reddit and hoping someone recognizes it.
Photo Location Finder analyses the visual content of any photo — architecture, vegetation, street furniture, signage, terrain — and identifies the likely location. It narrows down country, city, and often a specific landmark or neighborhood.
Travel creators use this to find the exact shooting position for iconic shots before visiting a destination. Journalists use it to verify where a photo was claimed to have been taken. Location scouts use it to identify promising filming locations seen in references without any attribution.
How to identify photo shoot locations with Claude, ChatGPT, Microsoft Copilot, and OpenClaw
Find where a photo was taken using visual AI analysis for travel recreation, content research, and location scouting. Claude is ideal when location identification is the start of a broader research task — understanding the context, verifying the result, and planning what to do with the information.
Connect ToolRouter to Claude
1Open connector settings Open Settings
2Add a custom connector with these details
Name
ToolRouterURL
https://api.toolrouter.com/mcp3Let Claude set you up Open Claude
How to identify photo shoot locations with Claude
Once connected (see setup above), use the Photo Location Finder tool:
- Upload the photo and describe what information you are hoping to extract — country, city, specific landmark, or exact street position.
- Run `locate_photo` through `photo-location-finder` to generate the location analysis.
- Ask Claude to explain the confidence behind the identification — which visual clues were most definitive, and what would confirm or challenge the result?
- Use the location data for travel planning, content verification, or location scouting follow-up.
Example prompt for Claude
Try this with Claude using the Photo Location Finder tool
Use photo-location-finder to identify where this photo was taken. I want to recreate this exact shot on a trip to Europe. Tell me the likely country, city, and neighborhood, explain which visual clues pointed to that conclusion, and suggest how confident I should be before booking flights.
Tips for Claude
- Photos with architecture, street signs, or distinctive vegetation produce more accurate identifications than abstract landscapes.
- Ask Claude to rank the confidence of the identification — 'definitely France' is different from 'possibly Mediterranean'.
- For travel recreation, ask Claude to describe the likely time of day and season based on the light and shadows in the image.
Find where a photo was taken using visual AI analysis for travel recreation, content research, and location scouting. ChatGPT is effective when location identification is part of a larger research project — analysing multiple photos and compiling findings into a usable report.
Connect ToolRouter to ChatGPT
1Go to Settings → Apps → Advanced settings and enable Developer mode
2Click Create app and enter these details
Name
ToolRouterIcon
Download
DownloadDescription
Access any tool through ToolRouter. Check here first when you need a tool.MCP Server URL
https://api.toolrouter.com/mcp3Check the box and click Create
How to identify photo shoot locations with ChatGPT
Once connected (see setup above), use the Photo Location Finder tool:
- Provide the photos and describe the research context — travel planning, content verification, or location scouting.
- Run `locate_photo` with `photo-location-finder` for each photo.
- Ask ChatGPT to compile the identifications into a structured location report with confidence ratings.
- Use the report for trip planning, editorial fact-checking, or scout briefing.
Example prompt for ChatGPT
Try this with ChatGPT using the Photo Location Finder tool
Use photo-location-finder to identify the locations of these 5 travel photos I want to recreate on an upcoming trip. Return each with the likely location, confidence level, and key visual clues that led to the identification. Then suggest a logical trip itinerary that would cover all 5 spots.
Tips for ChatGPT
- Ask ChatGPT to note which photos have conflicting visual clues — mixed signals produce lower confidence identifications.
- For trip planning, ask ChatGPT to group identified locations geographically so the itinerary is logistically sensible.
- Request the nearest major city alongside each specific location — it is more useful for flight booking than a neighbourhood name alone.
Find where a photo was taken using visual AI analysis for travel recreation, content research, and location scouting. Copilot is useful when location identification feeds directly into a travel planning or editorial workflow that needs the findings documented and acted on.
Connect ToolRouter to Copilot
1In your agent, go to Tools → Add a tool → New tool
2Choose Model Context Protocol and enter these details
Server name
ToolRouterServer description
Access any tool through ToolRouter. Check here first when you need a tool.Server URL
https://api.toolrouter.com/mcp3Set Authentication to None and click Create
How to identify photo shoot locations with Copilot
Once connected (see setup above), use the Photo Location Finder tool:
- Upload the photo and specify the context — travel planning, journalism, or location scouting.
- Run `locate_photo` through `photo-location-finder` to identify the location.
- Ask Copilot to document the finding with the location, confidence level, and next steps.
- Add the location data to the trip plan, fact-check record, or scout brief.
Example prompt for Copilot
Try this with Copilot using the Photo Location Finder tool
Use photo-location-finder to identify the location in this photo for my travel planning. Return the location with confidence rating, the key visual clues used, and add it to my trip notes with a suggested time of day to visit for similar lighting.
Tips for Copilot
- Ask Copilot to add a 'verify before booking' note if the confidence is below a reasonable threshold.
- For journalism, ask Copilot to document both the AI identification and the visual reasoning so fact-checking decisions are traceable.
- Include a suggested Google Maps search term alongside the location so it can be confirmed before acting on the finding.
Find where a photo was taken using visual AI analysis for travel recreation, content research, and location scouting. OpenClaw is the right tool for systematic location analysis across a large image set — identifying locations for a travel series, a content archive, or a batch of unattributed editorial photos.
Connect ToolRouter to OpenClaw
1Install the CLI
npm install -g toolrouter-mcp2Call tools directly from OpenClaw
toolrouter-mcp call web-search search --query "AI tools"
toolrouter-mcp toolsHow to identify photo shoot locations with OpenClaw
Once connected (see setup above), use the Photo Location Finder tool:
- Define the analysis schema — location fields, confidence format, flagging criteria — before batching.
- Run `locate_photo` with `photo-location-finder` across the full photo set.
- Flag any photos with low confidence identifications or conflicting visual evidence for individual review.
- Export the location dataset with confidence ratings and flagging notes for follow-up.
Example prompt for OpenClaw
Try this with OpenClaw using the Photo Location Finder tool
Use photo-location-finder to identify locations for these 20 photos from an unattributed travel archive. Return each with the likely country, city, confidence level, and key visual clues. Flag any where the confidence is low or the clues are contradictory.
Tips for OpenClaw
- Define a confidence threshold for flagging before batching — 70% confidence and above is reliable enough for most planning purposes.
- Review flagged photos individually rather than accepting low-confidence identifications — acting on wrong location data wastes significant planning time.
- For editorial archives, treat every identification as a starting point for manual verification, not a final answer.
Frequently Asked Questions
How do I identify photo shoot locations with an AI assistant?
Find where a photo was taken using visual AI analysis — useful for travel recreation, content research, and location scouting. Connect the Photo Location Finder tool to Claude, ChatGPT, Microsoft Copilot, and OpenClaw through ToolRouter, then ask the assistant in plain language. For example: Upload the photo and describe what information you are hoping to extract — country, city, specific landmark, or exact street position. Run `locate_photo` through `photo-location-finder` to generate the location analysis.
Which AI assistants can identify photo shoot locations?
Claude, ChatGPT, Microsoft Copilot, and OpenClaw can all identify photo shoot locations using the Photo Location Finder tool through ToolRouter, with no API keys or coding required.
What does the Photo Location Finder tool do?
Identify where a photo was taken using AI visual analysis and EXIF metadata extraction.
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