Tools / Photo Location Finder / Use Cases / Extract Photo EXIF Metadata

Extract Photo EXIF Metadata

Read embedded EXIF data from photos — GPS coordinates, camera settings, date and time — for location verification and photography analysis.

Tool
Photo Location Finder icon
Photo Location Finder

Every 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.

Agent Guides

Claude

  1. Connect ToolRouter to Claude: claude mcp add toolrouter -- npx -y toolrouter-mcp
  2. Upload the image file and describe the metadata you are looking for — location, camera settings, or capture time.
  3. Run `read_exif` through `photo-location-finder` to extract the metadata.
Read full guide →

ChatGPT

  1. Add ToolRouter to ChatGPT using the MCP JSON configuration: {"mcpServers":{"toolrouter":{"command":"npx","args":["-y","toolrouter-mcp"]}}}
  2. Provide the image files and specify which metadata fields are most important.
  3. Run `read_exif` with `photo-location-finder` across the image set.
Read full guide →

Copilot

  1. Add ToolRouter to your Copilot MCP configuration: {"mcpServers":{"toolrouter":{"command":"npx","args":["-y","toolrouter-mcp"]}}}
  2. Upload the image and specify the metadata fields needed.
  3. Run `read_exif` through `photo-location-finder` to extract the data.
Read full guide →

OpenClaw

  1. Connect ToolRouter to OpenClaw: openclaw mcp add toolrouter -- npx -y toolrouter-mcp
  2. Define the metadata schema and output format before batching the image set.
  3. Run `read_exif` with `photo-location-finder` across the full image library.
Read full guide →

Related Use Cases

Open Identify Photo Shoot Locations

Identify Photo Shoot Locations

Find where a photo was taken using visual AI analysis — useful for travel recreation, content research, and location scouting.

Photo Location Finder icon
Photo Location Finder
4 agent guides