How to Use the Mnemonic MCP in Pydantic AI

Validate every NFT market response with Mnemonic and Pydantic AI for type-safe, error-free agent logic.

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Connect Mnemonic MCP to Pydantic AI

Create your Vinkius account to connect Mnemonic 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 Mnemonic with Pydantic AI

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Perplexity

Type-safe NFT data for Pydantic AI

Every response from `get_nft_details` is validated against your Pydantic models at runtime. If the chain returns malformed data, your agent catches it immediately. This prevents silent failures in your logic. You get reliable, typed data every time you call a tool.

Strict schema enforcement

Use `get_collection_stats` to feed your agent structured market data. Pydantic AI ensures the fields match your expected types before any processing starts. It eliminates hallucinations caused by unexpected API responses. Your agent operates on verified, clean data structures.

Reliable wallet transaction analysis

Query `get_wallet_history` and let your agent perform complex audits. The runtime validation ensures that transaction records are formatted correctly for your analysis. It makes your agent code predictable and easier to debug. You spend less time fixing data errors and more time refining your logic.

Setup guide

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

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

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

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Common questions about Mnemonic MCP in Pydantic AI

Yes. The server outputs are compatible with your Pydantic models, enabling strict runtime validation for all tool responses.

Install the MCP support package and pass the server URL to your agent configuration. It's built to work out of the box.

Only if the data is invalid. If that happens, the agent fails with a clear validation error, which is better than processing bad data.

It is. The connection handles async communication, matching the non-blocking requirements of your agent framework.

The server fetches data based on your specific requests. No user-sensitive private keys are ever handled by the tools, keeping your wallet data separate.

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