How to Use the Yelp Fusion MCP in Pydantic AI

Q: How do I search for businesses using Yelp Fusion and Pydantic AI?

You invoke searchbusinesses with your criteria. The resulting JSON is immediately validated by the framework, guaranteeing that every returned field (like name and category) matches the Python type you specified.

Q: Can Yelp Fusion help me find job types using Pydantic AI?

Yes. You can use getjobs to translate natural language into service categories. The strong typing ensures that even if the underlying API changes, your agent's expected input/output structure remains correct.

Q: What kind of event data does Yelp Fusion support with Pydantic AI?

The geteventdetails tool retrieves detailed info. Because of runtime validation, you know exactly what fields (start date, location coordinates, etc.) are available and correctly typed for your application.

Q: If I use Yelp Fusion to get business details with Pydantic AI, is the data reliable?

It's highly reliable. getbusinessdetails provides rich information that gets validated at runtime. This means if the API sends bad data, your agent stops and tells you, instead of letting a calculation fail silently.

Build validated agents that retrieve Yelp Fusion data with Pydantic AI for guaranteed type correctness.

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Connect Yelp Fusion MCP to Pydantic AI

Create your Vinkius account to connect Yelp Fusion to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Yelp Fusion with Pydantic AI

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Validate Business Search Results

The `search_businesses` tool finds businesses, and because you're using Pydantic AI, every piece of returned data is validated against your defined schema. You never get unexpected fields. This capability means you can trust the input structure for downstream systems—no more silent corruption when an API changes its payload.

Structure Review Highlights

You use `get_review_highlights` to pull key takeaways from customer reviews. Pydantic validates this data, ensuring the output is always a predictable list of structured insights. This makes building consistent reporting dashboards simple; your agent's output format won't suddenly break because Yelp changed its backend.

Find Service Offerings with Type Safety

The `get_service_offerings` tool lists active services, and Pydantic enforces that the resulting data adheres to your model. If a field is missing or malformed, the agent fails loudly. Correctness trumps speed here. You get an explicit error instead of trying to process garbage data.

Setup guide

Set up Yelp Fusion MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "yelp-fusion-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Yelp Fusion tools.",
)

result = await agent.run("List recent Yelp Fusion transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Yelp Fusion. 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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Common questions about Yelp Fusion MCP in Pydantic AI

You invoke `search_businesses` with your criteria. The resulting JSON is immediately validated by the framework, guaranteeing that every returned field (like name and category) matches the Python type you specified.

Yes. You can use `get_jobs` to translate natural language into service categories. The strong typing ensures that even if the underlying API changes, your agent's expected input/output structure remains correct.

The `get_event_details` tool retrieves detailed info. Because of runtime validation, you know exactly what fields (start date, location coordinates, etc.) are available and correctly typed for your application.

It's highly reliable. `get_business_details` provides rich information that gets validated at runtime. This means if the API sends bad data, your agent stops and tells you, instead of letting a calculation fail silently.

The server handles business names, phone numbers, and review excerpts (string/numeric data). The type-safe approach ensures that when your agent processes this sensitive location data, it always expects the correct format.

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