Birdeye MCP. Manage reviews, check-ins, and feedback in one place.
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Birdeye MCP Server manages your online reputation and customer feedback. Use it to list reviews from Google and Facebook, send automated check-ins, and run custom surveys against your customer base.
It gives your AI agent full control over gathering and analyzing customer sentiment and location data for multi-site businesses.
What your AI agents can do
Create customer
Adds a new customer profile to your system.
Customer checkin
Triggers an automated review request (Check-in) to a customer.
Get customer details
Retrieves the full profile and detailed history for a specific customer.
List customer reviews across multiple platforms, retrieving detailed ratings and high-fidelity comments in real time.
Trigger review requests (Check-in) via SMS or email to collect feedback from recent visitors.
Dispatch custom surveys to specific customers and monitor their responses through the AI agent.
Create new customer profiles when an interaction occurs, keeping a record of the individual.
Fetch a customer's full profile, including detailed sentiment history and activity records.
Pull a complete directory of all your business branches and locations for coordinated management.
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Supported MCP Clients
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Birdeye MCP Server: 6 Tools for Reputation Management
These tools let your agent manage the entire customer lifecycle: creating profiles, requesting feedback, listing reviews, and running surveys.
019dd0c2create customer
Adds a new customer profile to your system.
019dd0c2customer checkin
Triggers an automated review request (Check-in) to a customer.
019dd0c2get customer details
Retrieves the full profile and detailed history for a specific customer.
019dd0c2list business locations
Lists all business locations and branches associated with your account.
019dd0c2list reviews
Retrieves a list of customer reviews from various platforms.
019dd0c2trigger survey
Sends a custom survey to a specified customer.
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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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- Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector
Birdeye MCP Server keeps tabs on your online reputation and customer feedback. Your AI agent uses this server to list customer reviews from Google and Facebook, send automated check-ins, and run custom surveys against your customer base. It gives your agent full control over gathering and analyzing customer sentiment and location data for multi-site businesses.
Gather and Analyze Reviews
Your agent can list customer reviews from multiple platforms, getting detailed ratings and high-fidelity comments in real time. You'll get a complete snapshot of your online feedback.
Send Automated Feedback Requests
It triggers an automated review request (Check-in) via SMS or email to collect feedback from recent visitors.
Send Targeted Surveys
Your agent dispatches custom surveys to specific customers and monitors their responses.
Build Customer Records
It adds a new customer profile to your system when an interaction happens, keeping a record of the individual.
Retrieve Customer History
It fetches a customer's full profile, including detailed sentiment history and activity records.
Map Business Locations
It pulls a complete directory of all your business branches and locations for coordinated management.
How Birdeye MCP Works
- 1 Subscribe to the server and grab your Birdeye API Key and Business ID (bid) from your Birdeye dashboard.
- 2 Your AI client connects to the server using the credentials.
- 3 You give a natural language command (e.g., 'Check the sentiment for John Doe'). The agent executes the relevant tool calls and returns the data.
The bottom line is, your AI client uses your API credentials to run Birdeye's tools, giving you a single place to manage customer reputation.
Who Is Birdeye MCP For?
Marketing managers, customer success teams, and multi-location owners need this. It solves the pain of manual reputation tracking, letting them manage customer feedback and location visibility without leaving their core workspace.
Uses the agent to instantly retrieve high-level review summaries and monitor brand sentiment across all locations using natural language commands.
Automates sending review requests (customer_checkin) and tracks customer satisfaction without having to switch between internal tools and review platforms.
Coordinates reputation performance across multiple branches, retrieving location lists and running targeted surveys through simple AI queries.
What Changes When You Connect
- Review data moves from scattered tabs to a single conversation thread. You can run
list_reviewsand immediately see the feedback alongside customer data. - Automate follow-ups. Instead of manual emails, use
customer_checkinto trigger review requests, keeping your feedback loop active. - Coordinate multi-site efforts. Use
list_business_locationsto pull all branch directories, then runlist_reviewsagainst the specific location ID. - Track sentiment over time.
get_customer_detailspulls the full customer profile, letting you see the history of sentiment changes, not just the last interaction. - Run targeted campaigns. Use
trigger_surveyto send custom feedback to high-value customers, and then monitor the results through your agent. - Keep data clean. Use
create_customerto ensure every customer interaction is logged and linked to a central profile.
Real-World Use Cases
A store opened a new branch and needs to track reviews.
The owner asks the agent to check reputation across all sites. The agent runs list_business_locations to get every branch ID, then loops through them, running list_reviews for each one. The owner gets a consolidated, cross-branch report instantly.
A high-value customer had a service issue.
The CS rep needs to understand the context. They use get_customer_details to pull the full profile, seeing the sentiment history. They then use trigger_survey to get specific feedback, ensuring the issue is documented and actionable.
The team needs to clean up its contact list.
A new customer walks in. The agent uses create_customer to log the interaction. If they leave a review, the agent immediately uses customer_checkin to prompt a follow-up review request.
Running a quarterly NPS campaign.
The manager needs to survey a list of users. They first run list_business_locations to scope the campaign, then use trigger_survey to send the custom questionnaire to the specific IDs.
The Tradeoffs
Using a single tool for multiple goals
Trying to pull a customer's reviews and their sentiment history by only calling list_reviews. You get the raw text, but no profile context or NPS score.
→
First, run get_customer_details to get the profile context and sentiment score. Then, run list_reviews to get the source data. This two-step process keeps the data linked and complete.
Ignoring the business context
Manually running customer_checkin without knowing if the customer is even logged in. You waste a request and get no useful data.
→
Always check the customer first. Use get_customer_details to confirm the profile exists and is active before running customer_checkin or trigger_survey.
Overlooking location scope
Trying to find reviews for 'Main St.' without first verifying the exact location ID. You get vague results or nothing at all.
→
Always start by running list_business_locations. This gives you the canonical IDs you need to scope the rest of your calls, like list_reviews.
When It Fits, When It Doesn't
Use this server if your primary job is managing customer reputation across multiple channels and locations. You need to track customer sentiment, manage follow-up requests, and pull cross-site review data. Don't use it if your goal is pure, single-channel analytics (e.g., only tracking web form submissions) or if you need complex billing/subscription management. If you only need to read reviews, a dedicated review API might suffice, but Birdeye gives you the full orchestration layer with get_customer_details and trigger_survey.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Birdeye. 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 6 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Reputation tracking used to mean logging into five different websites.
Before this, tracking customer feedback meant jumping between Google Maps, Facebook, and your internal CRM. You'd copy a review headline, paste it into a spreadsheet, and manually update a status column. It was slow, prone to copy/paste errors, and often missed the context.
Now, you just tell your agent to 'Show me the sentiment for last week's reviews.' Your agent runs the necessary tools and pulls the data from all sources, giving you a single, actionable report right in your chat window.
Birdeye MCP Server: Managing customer feedback in your chat.
You no longer need to manually send out review requests via separate email marketing platforms or track which customers responded. Your agent handles the whole process: it uses `customer_checkin` to send the request, and then tracks the follow-up status, all without leaving the chat.
Common Questions About Birdeye MCP
How do I get all customer reviews using list_reviews? +
The list_reviews tool pulls reviews from multiple sources, giving you a combined view. You can filter the results by date range or rating type to narrow down the focus.
Can I use customer_checkin to request reviews for a group of people? +
Currently, customer_checkin is designed to target a single customer. However, you can combine it with list_business_locations and iterate the process for multiple sites or customer IDs.
What is the difference between get_customer_details and list_reviews? +
get_customer_details gives you the customer's profile, including sentiment scores and activity history. list_reviews gives you a raw feed of public reviews, regardless of whether the customer profile exists in your system.
Does Birdeye MCP Server help with multi-location management? +
Yes. You use list_business_locations to retrieve all your branch IDs. You can then pass these IDs to other tools to coordinate campaigns across your entire organization.
How do I use list_business_locations to ensure I get all my company's branches? +
The list_business_locations tool retrieves a complete directory of every location tied to your Birdeye account. It ensures you can coordinate reputation efforts across all your physical or virtual branches.
What data does `get_customer_details` provide, and can I use it for sentiment analysis? +
get_customer_details provides a full customer profile, including detailed sentiment history and metrics. You can use this data to track brand health and identify patterns in customer feedback.
Can I use `trigger_survey` to send different surveys to different customer groups? +
Yes, you define the survey content and target specific customers when calling trigger_survey. This lets you send custom feedback forms to distinct groups based on your business needs.
When running `list_reviews`, what should I do if the response is incomplete or paginated? +
The list_reviews tool handles pagination automatically, giving you all available reviews in batches. Your agent will retrieve the full set of records, so you don't need to worry about incomplete data.
How do I find my Birdeye API Key and Business ID? +
Log in to your account, navigate to Settings > Integrations > API, and you will find your API Key and the Business ID (bid).
Can I request a review via AI? +
Yes! The customer_checkin tool allows your agent to record a customer visit and automatically send a review request via their preferred channel.
How do I check review ratings programmatically? +
Use the list_reviews tool and provide an optional rating filter (1-5) to retrieve specific categories of feedback directly from the platform.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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