Image Fetch Toolkit

Image Fetch Toolkit

A comprehensive guide for AI agents to search, retrieve, and curate images from various online sources. Covers free stock photos, academic figures, news images, product photos, scientific illustrations, and more.

Quick Start

Before fetching images, check which tools/APIs are available in the current environment:

1. Tavily - Web search + URL extraction (recommended, often pre-configured) 2. Unsplash API - 3M+ free high-quality photos 3. Pexels API - Free stock photos + videos 4. Pixabay API - 2M+ free images, illustrations, vectors 5. Flickr API - Photographer community images 6. Google Custom Search API - General image search 7. Bing Image Search API - Microsoft's image search

1. Free Stock Photo APIs

Unsplash API

# Search photos
curl -H "Authorization: Bearer $UNSPLASH_ACCESS_KEY" \
  "https://api.unsplash.com/search/photos?query=renewable+energy&per_page=10&orientation=landscape"
Get a random photo
curl -H "Authorization: Bearer $UNSPLASH_ACCESS_KEY" \
  "https://api.unsplash.com/photos/random?query=technology&orientation=squarish"
Download tracked photo (respects photographer attribution)
curl -H "Authorization: Bearer $UNSPLASH_ACCESS_KEY" \
  -L "https://api.unsplash.com/photos//download"

Response fields: results[].urls.raw, results[].urls.full, results[].urls.regular, results[].urls.small, results[].user.name, results[].links.html

Pexels API

# Search photos
curl -H "Authorization: $PEXELS_API_KEY" \
  "https://api.pexels.com/v1/search?query=nature&per_page=10&orientation=landscape"
Curated photos
curl -H "Authorization: $PEXELS_API_KEY" \
  "https://api.pexels.com/v1/curated?per_page=15"
Get photo by ID
curl -H "Authorization: $PEXELS_API_KEY" \
  "https://api.pexels.com/v1/photos/"

Pixabay API

# Search images
curl "https://pixabay.com/api/?key=$PIXABAY_API_KEY&q=mountain+landscape&image_type=photo&per_page=10&safesearch=true"
Search vectors/illustrations
curl "https://pixabay.com/api/?key=$PIXABAY_API_KEY&q=robot&image_type=vector&per_page=10"
Search videos
curl "https://pixabay.com/api/videos/?key=$PIXABAY_API_KEY&q=ocean&per_page=5"

Categories: backgrounds, fashion, nature, science, education, feelings, health, people, religion, places, animals, industry, computer, food, sports, transportation, travel, buildings, business, music

Flickr API

# Search photos (CC license only)
curl "https://api.flickr.com/services/rest/?method=flickr.photos.search&api_key=$FLICKR_API_KEY&text=sunset&license=1,2,4,5,9&per_page=10&format=json&nojsoncallback=1"
Get photo URL: https://farm{farm}.staticflickr.com/{server}/{id}_{secret}.jpg

2. Search Engine Image APIs

Google Custom Search API (Image Search)

# Search images
curl "https://www.googleapis.com/customsearch/v1?key=$GOOGLE_API_KEY&cx=$GOOGLE_CX&searchType=image&q=AI+conference+2024&num=10&imgSize=large"

Bing Image Search API

curl -H "Ocp-Apim-Subscription-Key: $BING_API_KEY" \
  "https://api.bing.microsoft.com/v7.0/images/search?q=cute+cats&count=10&imageType=Photo&size=Large"

Tavily Extract (for webpage images)

# Extract content + images from a URL
node ~/.openclaw/workspace/skills/tavily-search/scripts/extract.mjs "https://example.com/article" --include-images true

3. Academic & Scientific Image Sources

Paper Search MCP (MCP Server)

npx skills add openags/paper-search-mcp
or with uv:
uv tool install paper-search-mcp

# Search papers
curl "https://api.semanticscholar.org/graph/v1/paper/search?query=protein+folding&limit=10&fields=title,url,openAccessPdf"

Semantic Scholar API (Free)

# Search papers with figure references
curl "https://api.semanticscholar.org/graph/v1/paper/search?query=transformer+architecture&limit=5&fields=title,url,openAccessPdf,figures"

arXiv API (Free, no key needed)

# Search papers
curl "http://export.arxiv.org/api/query?search_query=all:electron+microscopy&start=0&max_results=5"

PubMed Central (Free, no key needed)

# Search PMC for figures
curl "https://www.ncbi.nlm.nih.gov/pmc/utils/oa/oa.fcgi?id=PMC1234567"  # get full text XML with figures

Scientific Illustration Tools

4. Academic Figure Composition (Multi-Panel abc Labels)

For combining multiple images into a single figure with (a), (b), (c) labels - standard in academic papers.

Python (matplotlib + PIL)

from PIL import Image, ImageDraw, ImageFont
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
def create_figure_grid(image_paths, labels=None, cols=2, label_font_size=20, 
                       label_position='top-left', padding=20, label_color='white',
                       bg_color='white', dpi=300, output_path='figure.png'):
    """
    Combine multiple images into a single academic figure with (a)(b)(c) labels.
    
    Args:
        image_paths: List of image file paths
        labels: List of label strings (default: a, b, c, ...)
        cols: Number of columns
        label_font_size: Font size for labels
        label_position: 'top-left', 'top-right', 'bottom-left', 'bottom-right'
        padding: Space between images in pixels
        label_color: Color of labels ('white' or 'black')
        bg_color: Background color
        dpi: Output DPI
        output_path: Output file path
    """
    if labels is None:
        labels = [chr(ord('a') + i) for i in range(len(image_paths))]
    
    rows = (len(image_paths) + cols - 1) // cols
    images = [Image.open(p).convert('RGB') for p in image_paths]
    
    # Find max dimensions
    max_w = max(img.width for img in images)
    max_h = max(img.height for img in images)
    
    # Create canvas
    total_w = cols * max_w + (cols + 1) * padding
    total_h = rows * max_h + (rows + 1) * padding
    canvas = Image.new('RGB', (total_w, total_h), bg_color)
    draw = ImageDraw.Draw(canvas)
    
    # Try to load a font
    try:
        font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf", label_font_size)
    except:
        font = ImageFont.load_default()
    
    for idx, (img, label) in enumerate(zip(images, labels)):
        row, col = idx // cols, idx % cols
        x = padding + col * (max_w + padding)
        y = padding + row * (max_h + padding)
        canvas.paste(img, (x, y))
        
        # Draw label
        label_text = f"({label})"
        bbox = draw.textbbox((0, 0), label_text, font=font)
        lw, lh = bbox[2] - bbox[0], bbox[3] - bbox[1]
        margin = 10
        
        if label_position == 'top-left':
            lx, ly = x + margin, y + margin
        elif label_position == 'top-right':
            lx, ly = x + max_w - lw - margin, y + margin
        elif label_position == 'bottom-left':
            lx, ly = x + margin, y + max_h - lh - margin
        else:
            lx, ly = x + max_w - lw - margin, y + max_h - lh - margin
        
        # Draw background rectangle for readability
        draw.rectangle([lx - 4, ly - 2, lx + lw + 4, ly + lh + 2], fill=label_color, outline=label_color)
        text_color = 'black' if label_color == 'white' else 'white'
        draw.text((lx, ly), label_text, fill=text_color, font=font)
    
    canvas.save(output_path, dpi=(dpi, dpi))
    print(f"Figure saved to {output_path}")
    return canvas
Usage
create_figure_grid(
    image_paths=['fig1.png', 'fig2.png', 'fig3.png', 'fig4.png'],
    labels=['a', 'b', 'c', 'd'],
    cols=2,
    output_path='combined_figure.png'
)

Python (matplotlib subplot)

import matplotlib.pyplot as plt
import matplotlib.image as mpimg
def subplot_figure(image_paths, labels=None, cols=2, figsize=(12, 10), 
                   label_size=16, label_weight='bold', output_path='figure.pdf'):
    """Create academic figure using matplotlib subplots with (a)(b)(c) labels."""
    if labels is None:
        labels = [chr(ord('a') + i) for i in range(len(image_paths))]
    
    rows = (len(image_paths) + cols - 1) // cols
    fig, axes = plt.subplots(rows, cols, figsize=figsize)
    axes = axes.flatten() if hasattr(axes, 'flatten') else [axes]
    
    for ax, path, label in zip(axes, image_paths, labels):
        img = mpimg.imread(path)
        ax.imshow(img)
        ax.set_title(f'({label})', fontsize=label_size, fontweight=label_weight, loc='left')
        ax.axis('off')
    
    # Hide empty subplots
    for ax in axes[len(image_paths):]:
        ax.axis('off')
    
    plt.tight_layout()
    fig.savefig(output_path, dpi=300, bbox_inches='tight')
    print(f"Saved to {output_path}")
Usage
subplot_figure(['a.png', 'b.png', 'c.png'], cols=3, output_path='fig1.pdf')

CLI one-liner (ImageMagick)

# Simple 2x2 grid
montage img1.png img2.png img3.png img4.png -tile 2x2 -geometry +5+5 output.png
With labels (requires additional steps)
Better to use the Python script above for labeled figures

5. News Image Sources

Google News Scraper

Tavily News Search

node ~/.openclaw/workspace/skills/tavily-search/scripts/search.mjs "AI breakthrough 2024" --topic news --days 7

NewsAPI.org

# Search news with images
curl "https://newsapi.org/v2/everything?q=AI+research&apiKey=$NEWSAPI_KEY&pageSize=10"
Articles include urlToImage field

GNews API

curl "https://gnews.io/api/v4/search?q=climate+change&token=$GNEWS_API_KEY&lang=en&max=10"

6. E-Commerce / Product Image Sources

Amazon Product Advertising API

# Search products with images (via PA-API)
curl -X POST "https://webservices.amazon.com/paapi5/searchitems" \
  -H "Content-Type: application/json" \
  -d '{"Keywords":"wireless headphones","SearchIndex":"Electronics","ItemCount":10}'

Scraper Alternatives (GitHub)

7. Social Media Image Sources

X/Twitter

Reddit

Instagram (via Meta Graph API)

8. Wikimedia Commons (Free, no key needed)

# Search images via MediaWiki API
curl "https://commons.wikimedia.org/w/api.php?action=query&generator=search&gsrnamespace=6&gsrsearch=cat+breeds&gsrlimit=10&prop=imageinfo&iiprop=url|extmetadata&format=json"
Get random featured picture
curl "https://commons.wikimedia.org/w/api.php?action=query&list=random&rnnamespace=6&rnlimit=5&prop=imageinfo&iiprop=url&format=json"

9. AI Image Generation (When You Can't Find What You Need)

Built-in OpenClaw image generation

MCP Image Generators

10. Image Search Strategy Guide

By Use Case

| Use Case | Best Sources | Notes | |----------|-------------|-------| | Academic papers | Semantic Scholar, arXiv, PubMed | Check open access for figures | | Blog posts | Unsplash, Pexels, Pixabay | Free commercial use | | Presentations | Unsplash, Wikimedia Commons | High resolution preferred | | Social media | Unsplash, Pexels, Pixabay | Square/vertical formats | | Product images | Platform APIs, scraper | Check ToS | | News articles | NewsAPI, Tavily news, Google News | urlToImage field | | Scientific figures | FigureLabs, BioRender, matplotlib | Generate, don't search | | Data visualizations | Reddit r/dataisbeautiful, Observable | Check licensing | | Icons/illustrations | Pixabay (vectors), Flaticon, Noun Project | SVG preferred | | Backgrounds | Unsplash, Pixabay (backgrounds category) | High resolution |

Best Practices

1. Always check licensing - Use CC0/public domain when possible for publications 2. Attribute creators - Even when not required, it's good practice 3. Prefer high resolution - Download raw or full size for print/publication 4. Batch your requests - Respect API rate limits 5. Cache results - Don't re-fetch the same images 6. Validate URLs - Image URLs can expire; download promptly 7. Use include_images - When extracting web content, request images

Environment Variable Reference

Set these in your shell environment or .env file:

# Free Stock Photos
UNSPLASH_ACCESS_KEY=""     # https://unsplash.com/developers
PEXELS_API_KEY=""          # https://www.pexels.com/api/
PIXABAY_API_KEY=""         # https://pixabay.com/api/docs/
FLICKR_API_KEY=""          # https://www.flickr.com/services/apps/
Search Engines
GOOGLE_API_KEY=""          # https://developers.google.com/custom-search
GOOGLE_CX=""               # Custom Search Engine ID
BING_API_KEY=""            # https://www.microsoft.com/en-us/bing/apis/
News
NEWSAPI_KEY=""             # https://newsapi.org
GNEWS_API_KEY=""           # https://gnews.io
AI Generation
GEMINI_API_KEY=""          # https://aistudio.google.com
OPENAI_API_KEY=""          # https://platform.openai.com

Before fetching images, check which tools/APIs are available in the current environment:

1. Tavily - Web search + URL extraction (recommended, often pre-configured) 2. Unsplash API - 3M+ free high-quality photos 3. Pexels API - Free stock photos + videos 4. Pixabay API - 2M+ free images, illustrations, vectors 5. Flickr API - Photographer community images 6. Google Custom Search API - General image search 7. Bing Image Search API - Microsoft's image search

1. Always check licensing - Use CC0/public domain when possible for publications 2. Attribute creators - Even when not required, it's good practice 3. Prefer high resolution - Download raw or full size for print/publication 4. Batch your requests - Respect API rate limits 5. Cache results - Don't re-fetch the same images 6. Validate URLs - Image URLs can expire; download promptly 7. Use include_images - When extracting web content, request images