Open Brewery DB MCP. Structured location data for every US-based brewery.
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Open Brewery DB MCP Server connects your AI agent directly to a structured database of U.S. breweries. It lets you search by name, filter results down to a specific city or state, and narrow the list by business type (micro, brewpub, etc.).
You get immediate access to addresses, phone numbers, and websites for every location.
What your AI agents can do
Find breweries by city
Finds all breweries located in a specific city name, great for local planning.
Find breweries by state
Locates every brewery operating within an entire US state by its full official name.
Find breweries by type
Filters the database based on business style, such as 'micro' or 'brewpub'.
Find breweries across the US using a general keyword or partial name.
Retrieves every known brewery location within a specified city boundary.
Gathers a full list of breweries operating anywhere in a designated US state.
Narrows down the search results to specific operational types, like nano or brewpub.
Pulls structured data including address, phone number, and website for every listed location.
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Open Brewery DB MCP Server: 4 Tools for Location Data Retrieval
Use these four tools to programmatically retrieve detailed location, contact, and type data for breweries across the United States.
019d75e8find breweries by city
Finds all breweries located in a specific city name, great for local planning.
019d75e8find breweries by state
Locates every brewery operating within an entire US state by its full official name.
019d75e8find breweries by type
Filters the database based on business style, such as 'micro' or 'brewpub'.
019d75e8search breweries
Searches for any brewery using a general keyword or partial name across all of the United States.
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.
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Make Your AI Do More
Start with Open Brewery DB, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
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- Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector
Your AI client connects directly to an open-source database covering U.S. breweries through this MCP Server. You don't have to scrape anything or guess parameters; your agent uses specific, structured tools to pull exactly what you need.
search_breweries: This tool lets your agent find any brewery using a general keyword or a partial name across the entire United States. If you know a brand name but not its exact location, running this query gets results from all matching entries nationwide. find_breweries_by_city: When you need to plan an itinerary for a specific local area, your agent executes this tool.
It returns every known brewery located within the city boundary you specify.
find_breweries_by_state: If you're mapping out coverage across a whole region, this tool works for you. You feed it the full official name of any US state, and your agent gathers a complete list of all breweries operating anywhere in that designated state boundary. find_breweries_by_type: Need to narrow down results by style? This tool filters the database based on specific operational types, like 'micro' or 'brewpub.' You can run this query to limit the search only to businesses that match your criteria.
When you call any of these tools—whether it’s a general keyword search, filtering by state, or listing all locations in Chicago—your agent automatically pulls structured data for every single entry. This output is robust: you get the full address, the phone number, the website URL, and even the precise GPS coordinates for every listed brewery.
You're building something that needs reliable contact details. You can pull out specific fields like the web link or the main phone number for any location found in the results set. The system handles the data retrieval so you don't have to worry about authentication or complex API calls. It just gives you clean, actionable data.
If your goal is simple local planning, let your agent use find_breweries_by_city. If you need massive coverage and are mapping out a whole state for research, run find_breweries_by_state. For a quick check on a brand name anywhere in the country, just hit up search_breweries. And if your dataset is huge and you only care about nano-brewery operations, find_breweries_by_type will cut through the noise.
You get immediate access to comprehensive location data without any guesswork.
How Open Brewery DB MCP Works
- 1 Your AI client sends a natural language prompt to your agent (e.g., 'I need micro-breweries in Denver').
- 2 The agent translates the intent, selecting and running multiple specialized tools (
find_breweries_by_cityandfind_breweries_by_type) sequentially. - 3 It returns a structured JSON payload containing all matching brewery names, addresses, and contact details.
The bottom line is: you get clean, predictable data from a US database without writing complex API calls yourself.
Who Is Open Brewery DB MCP For?
Anyone building location-based services for the travel or hospitality industry. You're the developer who can't afford to scrape Yelp and Google Maps manually, needing reliable, structured data on demand.
Needs a backend source of truth to populate guided tours or local discovery features. They use the tools to validate location coverage by state.
Builds booking widgets or event directories that require structured contact data (phone, address) for multiple businesses in one area.
Uses the tools to programmatically generate curated lists of specific types of venues (e.g., only nano-breweries) for themed tours.
What Changes When You Connect
- Skip manual database compilation. Instead of opening multiple websites (Yelp, Google Maps) to compile a list, your agent uses
find_breweries_by_cityto pull all relevant locations in one go. - Pinpoint specific venue types instantly. Use
find_breweries_by_typeto filter out noise and only see micro-breweries or brewpubs, which is impossible with standard keyword search tools. - Scale your coverage across the nation. Need a list of every location in Oregon? Run
find_breweries_by_state. It handles the entire state boundary reliably. - Handle ambiguous queries easily. If you only know a partial name or concept,
search_breweriescatches it without requiring exact city/state matches. - Get guaranteed structured data. Every result includes address, phone number, and website URL, so your agent doesn't have to guess which details are missing.
Real-World Use Cases
Planning a multi-city tour
A travel developer needs to build an itinerary covering three states. Instead of running three separate web searches, they use find_breweries_by_state for each state and then combine the structured results into one master data set.
Curating a themed list
A local guide needs to publish an article on 'The Best Nano-Breweries.' They use find_breweries_by_type first, then refine the results using find_breweries_by_city to keep the focus tight and accurate.
Building a directory lookup
An API requires rapid lookups of businesses by name. The agent uses search_breweries with only keywords, getting immediate hits for partial names that manual search would miss.
Verifying regional coverage
A company wants to know if they have enough partners in the South. They run find_breweries_by_state on Texas and Florida, getting a verifiable count of locations for planning purposes.
The Tradeoffs
Treating all searches as keyword-only.
A user tries to find 'brewpubs in Portland' only using search_breweries, which might give too many irrelevant results or fail if the name is slightly off.
→
Always combine tools. Run find_breweries_by_city first, and then run find_breweries_by_type against those results for precise targeting.
Assuming a single tool handles location scope.
A user needs to check all breweries in Colorado. They might only use the city filter (find_breweries_by_city) and miss half the state's locations.
→
If you need full state coverage, always use find_breweries_by_state. It’s designed for the entire boundary.
Manually cross-referencing data points.
Copying a brewery name from Google Maps and then searching for its phone number on Yelp, wasting time and risking outdated info.
→ Use any of the location tools. The resulting data payload includes the address, phone number, and website all in one clean block.
When It Fits, When It Doesn't
Use this MCP Server if your primary need is structured, verifiable location data for breweries across US states—for example, building a directory or running an itinerary service. The tools are perfect when you know the parameters (city name, state name, or business type). Don't use it if you just need to see the latest customer reviews; that requires a review aggregator tool instead. If your intent is purely exploratory ('What kind of beer do I want tonight?'), start with search_breweries for general ideas, then narrow down using specific filters like find_breweries_by_type.
It's designed to eliminate the friction between needing a list and actually getting structured data. It won’t give you subjective information (like 'best atmosphere'), but it will guarantee accuracy on objective details (address, phone).
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Open Brewery DB. 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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Works with 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 server provides 4 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Sifting through location data is slow. Copying addresses from Yelp or Google Maps wastes time.
Right now, building a comprehensive directory means opening dozens of tabs. You copy the name, then open another tab to find the address, and yet a third one for the phone number. It’s tedious, error-prone, and slows down your development cycle.
With this MCP Server, you just send the prompt: 'Give me all micro-breweries in Portland.' Your agent handles the entire data pull, returning structured JSON with every name, address, and contact detail in one go. That’s a huge time save.
Open Brewery DB MCP Server gives you structure for location data.
The biggest manual step that goes away is the need to coordinate three separate search calls (Name > City > Type). You can combine these filters in a single, logical workflow within your agent's prompt chain.
What’s different now is reliability. You aren't relying on scraping formats or API rate limits; you're querying a stable, open-source database designed for programmatic access.
Common Questions About Open Brewery DB MCP
How do I find all breweries in Colorado using the Open Brewery DB MCP Server? +
You use find_breweries_by_state. This tool targets the entire state boundary and returns every brewery found in Colorado, regardless of city.
Is there a way to find only nano-breweries? Open Brewery DB MCP Server? +
Yes. Use find_breweries_by_type. This tool lets you filter the entire database down to specific business styles like 'nano' or 'brewpub'.
Can I search for a brewery if I only remember part of the name? Open Brewery DB MCP Server? +
Absolutely. Use search_breweries. This tool handles general keywords and partial names, making it ideal when you're unsure of the exact spelling or full title.
Does Open Brewery DB MCP Server provide GPS coordinates? Open Brewery DB MCP Server? +
Yes. Every record returned by any tool includes the address, phone number, website, and precise GPS coordinates for planning purposes.
Does the Open Brewery DB MCP Server require any authentication keys or setup? +
No, it doesn't. The server runs with zero authentication required, making connection and testing immediate. You can connect your AI agent without needing to manage API credentials.
What happens if I call `find_breweries_by_city` too many times in a row? +
The server handles usage limits automatically. If you exceed the allowed rate, your agent will receive an explicit error response detailing the limit violation and when you can safely retry the function.
Can I combine filtering from `find_breweries_by_type` with a specific state? +
You must execute these calls sequentially. Pass the results or parameters gathered from the state search into the type filter's input to narrow down your dataset.
Is Open Brewery DB MCP Server compatible with multiple AI clients and platforms? +
Yes, because it uses the open Model Context Protocol (MCP) standard. Any client that supports MCP—like Claude or Cursor—can connect to and use the available tools directly.
What brewery types are available? +
Six types: micro (small-scale production), nano (ultra-small, often home-based), regional (large-scale distribution), brewpub (restaurant+brewery combo), contract (brewed at another location), and proprietor (owner-operated with minimal production).
Can I search for breweries by location coordinates? +
Yes, many entries in the Open Brewery DB include precise latitude and longitude coordinates, making it possible to query for breweries near a specific geographical point.
Are international breweries included? +
While the primary focus of Open Brewery DB has historically been the United States, it is actively expanding to include breweries from the UK, Ireland, South Korea, and other international locations.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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