Mnemonic MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Mnemonic as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Mnemonic. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Mnemonic?"
)
print(response)
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.
LlamaIndex agents combine Mnemonic tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Mnemonic MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the Mnemonic MCP Server
LlamaIndex provides unique advantages when paired with Mnemonic through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Mnemonic tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Mnemonic tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Mnemonic, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Mnemonic tools were called, what data was returned, and how it influenced the final answer
Mnemonic + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Mnemonic MCP Server delivers measurable value.
Hybrid search: combine Mnemonic real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Mnemonic to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Mnemonic for fresh data
Analytical workflows: chain Mnemonic queries with LlamaIndex's data connectors to build multi-source analytical reports
Mnemonic MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Mnemonic to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Mnemonic to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMnemonic + LlamaIndex FAQ
Common questions about integrating Mnemonic MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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 LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.