Can I reply to a review using the agent?

Yes! Use the `reply_to_review` tool with the Review ID and your message. If the source allows API replies, your message will be posted to Birdeye instantly.

How do I see the average rating for my business?

Simply ask the agent to `get_review_summary`. It will retrieve the overall counts and ratings aggregated across all supported platforms (Google, Facebook, etc.).

Can I trigger a review request for a specific customer?

Yes. Use the `checkin_customer` action with the customer's name and email. This will trigger the automated review and survey sequence configured in your Birdeye account.

Birdeye MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Birdeye
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Birdeye through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Birdeye "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Birdeye?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Birdeye MCP Server

Connect your Birdeye account to any AI agent and orchestrate your customer experience and reputation management workflows through natural conversation.

Pydantic AI validates every Birdeye tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Review Management — List and retrieve detailed customer reviews and fetch review summaries by source.
Customer Interaction — Reply to reviews directly from the agent to maintain high engagement.
CX Automation — Trigger customer check-ins to automatically send review or survey requests.
Survey Insights — List available surveys and retrieve customer responses for analysis.
Contact Oversight — Manage your business contacts and retrieve detailed profile information.
Location Tracking — Access and list all business locations managed within your account.

The Birdeye MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Birdeye to Pydantic AI via MCP

Follow these steps to integrate the Birdeye MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Birdeye with type-safe schemas

Why Use Pydantic AI with the Birdeye MCP Server

Pydantic AI provides unique advantages when paired with Birdeye through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Birdeye integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Birdeye connection logic from agent behavior for testable, maintainable code

Birdeye + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Birdeye MCP Server delivers measurable value.

Type-safe data pipelines: query Birdeye with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Birdeye tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Birdeye and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Birdeye responses and write comprehensive agent tests

Birdeye MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Birdeye to Pydantic AI via MCP:

checkin_customer

Check-in a customer to trigger review/survey requests

get_business_info

Retrieve core business information

get_contact

Get specific contact details

get_review_summary

Get a summary of review counts by source

get_survey_responses

Get responses for a specific survey

list_contacts

List customer contacts

list_locations

List all business locations

list_reviews

List customer reviews

list_surveys

List all surveys

reply_to_review

Reply to a specific customer review

Example Prompts for Birdeye in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Birdeye immediately.

"List the last 5 reviews received on Birdeye."

"Check in a customer: John Doe, john@example.com."

"Show my survey responses for survey surv_123."

Troubleshooting Birdeye MCP Server with Pydantic AI

Common issues when connecting Birdeye to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Birdeye + Pydantic AI FAQ

Common questions about integrating Birdeye MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Birdeye MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.