How to Use the Dextools (DeFi Token Data API) MCP in Pydantic AI

Q: How do I add Dextools (DeFi Token Data API) to my Pydantic AI project?

Install the pydantic-ai-slimmcp package and initialize an MCPToolset with your server URL. Pass this toolset into your Agent to start using the tools.

Get type-safe DeFi data for your Pydantic AI agent using this MCP Server.

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Connect Dextools (DeFi Token Data API) MCP to Pydantic AI

Create your Vinkius account to connect Dextools (DeFi Token Data API) 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 Dextools (DeFi Token Data API) with Pydantic AI

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Perplexity

Type-safe market data for your Pydantic AI agent

Every response from `get_token_price` and `get_token_liquidity` is validated against Pydantic models at runtime. If the API returns unexpected data, your agent catches it immediately. This prevents silent failures in your agent's logic. You get a reliable data stream that adheres strictly to your defined schemas, ensuring your agent logic remains predictable.

Reliable blockchain and pair lookups

Your agent can now use `get_blockchains` and `get_pair` to retrieve data with full type safety. The Pydantic AI framework ensures all returned fields match your expected types. This eliminates the risk of hallucinated fields or malformed data. Your agent operates on verified structures, making your DeFi integrations much more stable.

Validated token metadata for every request

The `get_token` tool provides structured information that your agent validates before taking any action. This adds a layer of safety to your Pydantic AI workflow. Because the data is validated at the boundary, your agent's decision-making process is protected from bad input. It ensures you maintain high standards for data integrity.

Setup guide

Set up Dextools (DeFi Token Data API) 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": {
        "dextools-defi-token-data-api-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Dextools (DeFi Token Data API) transactions")
print(result.output)

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Common questions about Dextools (DeFi Token Data API) MCP in Pydantic AI

Install the pydantic-ai-slim[mcp] package and initialize an MCPToolset with your server URL. Pass this toolset into your Agent to start using the tools.

Yes, every response is checked against your models. If the data structure deviates from your definition, Pydantic AI triggers a validation error.

Since the framework is model-agnostic, you can use any LLM you prefer. The toolset integration remains consistent regardless of the model you select.

The server runs externally and the toolset connects via HTTP or SSE. This allows for stable, long-running connections suitable for production agents.

The server is strictly limited to public token market data. It never interacts with private keys or account balances, ensuring your agent's scope remains secure.

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