Identify Photo Shoot Locations
Find where a photo was taken using visual AI analysis — useful for travel recreation, content research, and location scouting.
Extract Photo EXIF Metadata
Read embedded EXIF data from photos — GPS coordinates, camera settings, date and time — for location verification and photography analysis.
Quick answer: Use the Photo Location Finder tool through ToolRouter to extract photo exif metadata directly from Claude, ChatGPT, Microsoft Copilot, and OpenClaw — connect once, then drive it with plain-language prompts. No code required.
ToolEvery photo taken on a modern device contains hidden metadata — GPS coordinates, camera model, ISO, shutter speed, aperture, and the exact date and time of capture. Most people do not know how to access this information, and many photo platforms strip it before display.
Photo Location Finder reads the raw EXIF data embedded in any image file and returns it in a readable format. When GPS data is present, it translates raw coordinates into a human-readable location. When camera settings are present, it returns the full technical capture context.
Photographers use this to verify technical settings when recreating a shot. Legal and forensics professionals use it to establish when and where images were captured. Social media managers use it to confirm photo metadata before publishing to avoid unintentional privacy exposure.
How to extract photo exif metadata with Claude, ChatGPT, Microsoft Copilot, and OpenClaw
Read embedded EXIF data from photos — GPS coordinates, camera settings, and capture timestamps. Claude is ideal when EXIF extraction is the starting point of an analysis task — interpreting what the metadata means and deciding what to do with it.
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 extract photo exif metadata with Claude
Once connected (see setup above), use the Photo Location Finder tool:
- Upload the image file and describe the metadata you are looking for — location, camera settings, or capture time.
- Run `read_exif` through `photo-location-finder` to extract the metadata.
- Ask Claude to interpret the findings — what does the GPS data tell you, what do the camera settings suggest about the shooting conditions?
- Use the metadata for photography analysis, location verification, or forensic documentation.
Example prompt for Claude
Try this with Claude using the Photo Location Finder tool
Use photo-location-finder to read the EXIF data from this photo. I want to know the GPS coordinates, the date and time it was taken, and the camera settings used. Then tell me what the settings suggest about the shooting conditions and translate the GPS coordinates to a readable location.
Tips for Claude
- EXIF GPS data is only present if location was enabled when the photo was taken — many cameras and phone settings strip it by default.
- Ask Claude to translate GPS coordinates to a human-readable address or landmark, not just raw decimal degrees.
- For photography recreation, ask Claude to interpret the aperture, ISO, and shutter speed in plain language — 'bright midday outdoor light, no flash'.
Read embedded EXIF data from photos — GPS coordinates, camera settings, and capture timestamps. ChatGPT is effective when EXIF extraction is part of a batch analysis — reading metadata across multiple images and compiling the findings.
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 extract photo exif metadata with ChatGPT
Once connected (see setup above), use the Photo Location Finder tool:
- Provide the image files and specify which metadata fields are most important.
- Run `read_exif` with `photo-location-finder` across the image set.
- Ask ChatGPT to compile the metadata into a structured table and flag any images that are missing key fields.
- Use the compiled metadata for analysis, archiving, or verification.
Example prompt for ChatGPT
Try this with ChatGPT using the Photo Location Finder tool
Use photo-location-finder to extract EXIF data from these 8 photos. Return a table with filename, GPS location (human-readable), capture date and time, and camera model. Flag any photos where the GPS data is missing.
Tips for ChatGPT
- Ask ChatGPT to note when GPS data is absent and whether the capture date is still reliable — the two fields are independent.
- For photo archive management, ask ChatGPT to group photos by capture date and location from the EXIF data.
- Specify whether you want raw values or human-readable interpretations — both can be useful in different contexts.
Read embedded EXIF data from photos — GPS coordinates, camera settings, and capture timestamps. Copilot is useful when EXIF extraction feeds directly into a documentation or archiving workflow.
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 extract photo exif metadata with Copilot
Once connected (see setup above), use the Photo Location Finder tool:
- Upload the image and specify the metadata fields needed.
- Run `read_exif` through `photo-location-finder` to extract the data.
- Ask Copilot to format the metadata as a structured record for the archive or documentation system.
- File the metadata record alongside the image in the archive.
Example prompt for Copilot
Try this with Copilot using the Photo Location Finder tool
Use photo-location-finder to extract EXIF metadata from this photo for our image archive. Format the output as a structured record with filename, capture date, GPS location (human-readable), and camera settings. I'll add this to our photo library database.
Tips for Copilot
- Define the archive record format before extracting so metadata maps directly to the database fields.
- Ask Copilot to flag photos where EXIF data is incomplete — missing location or timestamp is an incomplete archive record.
- For privacy-sensitive workflows, note whether GPS data is present before sharing photos externally — EXIF location data survives most file transfers.
Read embedded EXIF data from photos — GPS coordinates, camera settings, and capture timestamps. OpenClaw is the right tool for bulk EXIF extraction — reading metadata across large photo archives or event libraries.
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 extract photo exif metadata with OpenClaw
Once connected (see setup above), use the Photo Location Finder tool:
- Define the metadata schema and output format before batching the image set.
- Run `read_exif` with `photo-location-finder` across the full image library.
- Flag any images with missing key fields — GPS, capture date, or camera model — for manual review.
- Export the full metadata dataset in the schema format for the archive system.
Example prompt for OpenClaw
Try this with OpenClaw using the Photo Location Finder tool
Use photo-location-finder to extract EXIF metadata from all 50 photos in this event archive. Return a structured table with filename, capture timestamp, GPS location where available, and camera model. Flag any photos where GPS data is absent.
Tips for OpenClaw
- Define which fields are mandatory before batching — it determines what counts as a flagged record.
- Sort the output by capture timestamp after extraction to produce a chronological archive view automatically.
- For event archives, GPS presence often varies by photographer device — flag and note this rather than treating absent GPS as an error.
Frequently Asked Questions
How do I extract photo exif metadata with an AI assistant?
Read embedded EXIF data from photos — GPS coordinates, camera settings, date and time — for location verification and photography analysis. 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 image file and describe the metadata you are looking for — location, camera settings, or capture time. Run `read_exif` through `photo-location-finder` to extract the metadata.
Which AI assistants can extract photo exif metadata?
Claude, ChatGPT, Microsoft Copilot, and OpenClaw can all extract photo exif metadata 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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