Mnemonic MCP Server for Pydantic AI 12 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Mnemonic through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Mnemonic "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Mnemonic?"
)
print(result.data)
asyncio.run(main())
* 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 Mnemonic MCP Server
Connect your Mnemonic account to your AI agent and unlock deep insights into the NFT ecosystem and Web3 data through natural conversation.
Pydantic AI validates every Mnemonic tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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
- Portfolio Tracking — List all NFTs owned by any wallet address and view their complete historical activity.
- Collection Analytics — Get real-time stats including floor price, volume, market cap, and ownership distribution.
- Market Pricing — Access real-time and historical pricing data for tokens across major marketplaces.
- Transfer Monitoring — Query historical transfer events for specific tokens or entire collections with advanced filters.
- Token Inspection — Retrieve complete metadata, properties, and current owners for any specific NFT.
- Smart Contract Data — Fetch detailed technical metadata for blockchain smart contracts and collections.
The Mnemonic MCP Server exposes 12 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 Mnemonic to Pydantic AI via MCP
Follow these steps to integrate the Mnemonic 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 12 tools from Mnemonic with type-safe schemas
Why Use Pydantic AI with the Mnemonic MCP Server
Pydantic AI provides unique advantages when paired with Mnemonic 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 Mnemonic integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Mnemonic connection logic from agent behavior for testable, maintainable code
Mnemonic + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Mnemonic MCP Server delivers measurable value.
Type-safe data pipelines: query Mnemonic with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Mnemonic tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Mnemonic and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Mnemonic responses and write comprehensive agent tests
Mnemonic MCP Tools for Pydantic AI (12)
These 12 tools become available when you connect Mnemonic to Pydantic AI via MCP:
get_collection_details
Get NFT collection info
get_collection_distribution
Get ownership distribution
get_collection_stats
Get collection statistics
get_contract_metadata
Get smart contract metadata
get_nft_details
Get detailed NFT metadata
get_nft_owners
Get owners of an NFT
get_nft_prices
Get NFT market pricing data
get_wallet_history
Get wallet transaction history
get_wallet_nfts
Get all NFTs owned by a wallet
list_collection_tokens
List tokens in a collection
list_transfers
Query NFT transfer events
search_collections
Search for NFT collections
Example Prompts for Mnemonic in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Mnemonic immediately.
"List all NFTs owned by the wallet 0x123..."
"Search for NFT collections named 'Cool Cats'."
"What is the ownership distribution for the Azuki collection?"
Troubleshooting Mnemonic MCP Server with Pydantic AI
Common issues when connecting Mnemonic to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiMnemonic + Pydantic AI FAQ
Common questions about integrating Mnemonic MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect Mnemonic with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Mnemonic to Pydantic AI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.