Flickr MCP for AI. Search millions of photos and extract their metadata.
Works with every AI agent you already use
…and any MCP-compatible client








How this MCP server connects to your AI agent
Flickr allows you to search millions of community photos and extract deep metadata about any image. Find visuals using tags, specific dates, or geographic coordinates.
Get titles, descriptions, and user details for public photosets and individual pictures.
What AI agents can do with Flickr Automation
Get person info
Pulls basic profile details like locations and stats for a Flickr user.
Get photo info
Retrieves the full metadata package—title, description, technical specs—for a single photo ID.
List photosets
Lists all public albums associated with a specific user account.
Find photos across the entire platform using keywords, tags, or specific geographic bounding boxes.
Retrieve full metadata for any public image, including its title, description, and technical camera specs.
List all the publicly shared albums belonging to a specific Flickr user account.
Pull profile information, location history, and general statistics for any known Flickr user.
Ask an AI about this
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What AI agents can do with Flickr Alternative: 5 Tools
These tools let you perform advanced searches on Flickr, retrieve specific photo details, map user albums, and check profile information.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Flickr on VinkiusGet Person Info
Pulls basic profile details like locations and stats for a Flickr user.
Get Photo Info
Retrieves the full metadata package—title, description, technical specs—for a single...
List Photosets
Lists all public albums associated with a specific user account.
Search Photos
Searches the entire Flickr library using keywords, tags, or defined date ranges.
Test Echo
Reflects back all parameters you pass to it; use this for testing connectivity.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Flickr, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Flickr. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Built on the Model Context Protocol (MCP) for Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 5 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Sifting through visual archives manually is a huge time drain.
Right now, if you want to find out what photos were taken at a specific landmark years ago, you have to jump between search result pages, clicking into each image just to check the date or coordinates. Then, you copy that data and paste it somewhere else.
With this MCP connected via Vinkius, your agent handles the whole loop. You tell it the criteria—location, time, tags—and it pulls all the necessary metadata directly from the source, giving you organized results without ever touching a manual search page.
Getting rich image data with `get_photo_info`
Instead of just seeing a picture thumbnail and guessing what it's about, you can now ask for the full details. This means getting the original title, the description written by the user, and even technical camera specs—all in one shot.
This changes everything because you don't have to trust secondary sources or guess at context. You get the actual data payload, making your content curation instantly more reliable.
What your AI can actually do with this
Need to dig through massive photo libraries but don't want the manual clicking? This MCP connects your agent directly to one of the largest global photo databases. You can search for images using simple tags or even by precise location coordinates. Want to know who posted it, or what camera was used? Fetch detailed metadata and user profiles in a single query.
When you connect this MCP through Vinkius, your AI client treats the Flickr API like just another set of data sources available at your fingertips, letting your agent handle all the heavy lifting.
019e5d1a-7a31-72c0-905f-8eaf88c19640 Here's how it actually works
The bottom line is you stop building custom API connectors for image services; your agent just knows how to use this one.
Subscribe to this MCP and input your personal Flickr API key into the Vinkius catalog.
Your AI client sends a query (like 'find all photos from NYC last month') to the connected service.
The MCP executes the request, processes the data, and passes back structured results detailing the photos or user info.
Who is this actually for?
Anyone who works with visual data—from marketing copywriters needing stock imagery to researchers tracking historical geography. You're the person staring at a dashboard full of links, knowing you have to manually click into each image one by one just to get the date or location details.
Finds visual inspiration and reference images for campaigns using specific tags or text searches.
Gathers geographic visual data and metadata to build timelines or maps based on photo locations and dates.
Tests API connectivity and builds prototypes that require rich, public image metadata for display.
What Changes When You Connect
Stop guessing what images exist. Use search_photos to find visuals using specific tags, text searches, or precise geographic coordinates.
Don't waste time copying data fields. With get_photo_info, you get the full technical metadata—titles, descriptions, and camera models—for any public photo ID.
Need to know what a user posted? You can use list_photosets to pull all their publicly shared albums in one go.
Build profiles on people. Use get_person_info to gather basic statistics and location data about the Flickr user who posted content.
Test connectivity instantly. If you're building something complex, run a simple check with test_echo before deploying your final query.
See it in action
Curating a historical gallery
A researcher needs photos from New Orleans between 1920 and 1930. They ask their agent to run search_photos using the date range filter and location bounding boxes, gathering hundreds of visual references instantly.
Competitive content analysis
A marketing team wants to see what photos competitors are posting. They use list_photosets on a known user ID to find all public albums, then run get_photo_info on the top images to pull metadata and understand their visual narrative.
Building a location data tool
A developer needs to verify if photos exist at a precise spot. They use search_photos with latitude/longitude coordinates to check for relevant content, then pass the resulting IDs into get_photo_info.
User profiling for inspiration
A creative director needs mood boards from a niche user. They first run get_person_info to verify the user exists, and then use list_photosets to get all their collection titles.
The honest tradeoffs
Searching only by keywords
Asking the agent for 'sunset pictures' without specifying a date or location. You get thousands of results, and you have to manually filter them.
Be precise. Use search_photos and provide both a keyword ('sunset') AND a specific time frame (e.g., bounding box coordinates) to narrow the search down immediately.
Assuming all data is visible
Trying to get deep technical info on an image without knowing its ID or relying solely on public view counts.
Always use get_photo_info after finding a candidate photo. This tool guarantees you retrieve the detailed metadata packet, like camera type and title.
Ignoring user boundaries
Asking for 'all photos' without first identifying the source or album collection.
Start by running list_photosets on a known user ID. This limits your scope to only their public collections, making the search manageable.
When It Fits, When It Doesn't
Use this MCP if your goal is pure visual research: finding images, extracting metadata, or mapping out photo collections based on who posted them and where they were taken. Don't use it if you need to manage private accounts; this only accesses public data. Also, don't use it just for simple keyword searching—if all you need is a general list of tags, your agent can handle that without needing the full search suite. However, if you absolutely must filter by date range or location coordinates, this MCP is necessary because those filters are handled specifically via search_photos and aren't available in other catalog tools.
Questions you might have
How does `search_photos` work with locations? +
search_photos allows you to filter results using bounding boxes (latitude and longitude). This lets your agent find visual content from a precise physical area, not just based on keywords.
What can I get using `list_photosets`? +
list_photosets returns all the public albums belonging to a specific user. This lets you map out the complete scope of content that individual has curated for public viewing.
Do I need `get_photo_info` every time? +
You only need get_photo_info when you've found a photo ID and require its deep technical metadata. A simple search might just give you the basics.
`test_echo` is for what? +
test_echo is purely for testing your setup. It reflects back all parameters you pass to it, confirming that your MCP connection and API keys are working correctly before running a real query.
What do I need to set up before using `get_person_info`? +
You must provide a valid Flickr API Key. This key authenticates your connection and ensures that your agent has the necessary permissions to retrieve user-specific data from the platform.
If I run complex searches with `search_photos`, how are rate limits handled? +
Flickr enforces usage quotas on API calls. Your AI client manages standard throttling, but if you exceed your key's allotted limit, the request will fail until the quota resets or you adjust your permissions.
What specific technical details does `get_photo_info` retrieve? +
It pulls detailed metadata beyond titles and descriptions. This includes camera models, lens information, GPS coordinates (if provided), and the exact date/time the photo was taken.
Is there a way to get user profile details using `list_photosets`? +
No, list_photosets only returns public album IDs and names. To gather detailed statistics or location data about the owner of those albums, you need to use the dedicated get_person_info tool.
Can I search for photos within a specific geographic area? +
Yes. Use the search_photos tool with the lat and lon parameters for radial queries, or the bbox parameter to define a specific rectangular bounding box.
How do I get the username and location of a Flickr member? +
You can use the get_person_info tool by providing the user's NSID (user_id). It will return their profile details, including username, real name, and location if public.
Is there a way to verify my API key is working correctly? +
Yes, you can use the test_echo tool. It simply echoes back any parameters you send, allowing you to confirm that the connection to the Flickr API is active.
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