Mnemonic MCP Server for LangChain 12 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Mnemonic through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"mnemonic": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Mnemonic, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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.
LangChain's ecosystem of 500+ components combines seamlessly with Mnemonic through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the Mnemonic MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 12 tools from Mnemonic via MCP
Why Use LangChain with the Mnemonic MCP Server
LangChain provides unique advantages when paired with Mnemonic through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Mnemonic MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Mnemonic queries for multi-turn workflows
Mnemonic + LangChain Use Cases
Practical scenarios where LangChain combined with the Mnemonic MCP Server delivers measurable value.
RAG with live data: combine Mnemonic tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Mnemonic, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Mnemonic tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Mnemonic tool call, measure latency, and optimize your agent's performance
Mnemonic MCP Tools for LangChain (12)
These 12 tools become available when you connect Mnemonic to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting Mnemonic to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersMnemonic + LangChain FAQ
Common questions about integrating Mnemonic MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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 LangChain
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.