How to Use the CoinGecko MCP in Pydantic AI

Q: How do I connect CoinGecko to Pydantic AI?

Use the MCPToolset class and provide the HTTP URL. It supports SSE or streaming HTTP connections for your agent.

Strictly typed crypto data from CoinGecko for your Pydantic AI agent workflows.

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Connect CoinGecko MCP to Pydantic AI

Create your Vinkius account to connect CoinGecko 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 CoinGecko with Pydantic AI

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Perplexity

Type-safe price checks for Pydantic AI

Use `get_price` to bring crypto values into your agent safely. Pydantic AI validates every returned value against your schema. If the API returns junk, the validation fails immediately. You never have to worry about the agent acting on corrupt data types.

Search assets using the CoinGecko MCP Server

Implement `search_crypto` to find token IDs reliably. Every search result is cast to a model, ensuring your agent logic stays predictable. This is ideal for production systems where you can't afford runtime errors. The agent fails loud, saving you hours of debugging hidden issues.

Retrieve market lists with Pydantic AI

Call `list_markets` to populate your internal data models. The tool response is strictly checked before your agent touches it. This architecture keeps your logic clean. You define the structure, and the MCP server provides the data that matches it perfectly.

Setup guide

Set up CoinGecko 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": {
        "coingecko-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about CoinGecko MCP in Pydantic AI

Yes. Every tool response is validated against your Pydantic models at runtime. It stops the agent if the data structure is invalid.

Use the `MCPToolset` class and provide the HTTP URL. It supports SSE or streaming HTTP connections for your agent.

Yes. The framework is model-agnostic. Whether you use OpenAI or a local model, the validation happens on your end.

Your agent throws a validation error. This prevents corrupted data from polluting your state or decision logic.

All requests are scoped to your active session. The ephemeral nature of the server ensures that no historical market data persists in our infrastructure.

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