Toket MCP Server for LlamaIndexGive LlamaIndex instant access to 8 tools to Create Collection, Easy Mint, Get Collection, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Toket 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 App Connector for LlamaIndex
The Toket app connector for LlamaIndex is a standout in the Ecommerce category — giving your AI agent 8 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Toket. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Toket?"
)
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 Toket MCP Server
Connect your Toket account to any AI agent and simplify how you deploy NFT collections, mint digital assets, and monitor blockchain interactions through natural conversation.
LlamaIndex agents combine Toket tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- Collection Management — List all your NFT collections and deploy new ERC-721 smart contracts instantly via AI.
- Asset Minting — Mint NFTs into specific collections or use 'Easy Mint' to quickly generate assets for recipients.
- Transaction Oversight — List and check the status of minting transactions to ensure successful blockchain delivery.
- Gas Management — Monitor your Gas Tank balance to keep your automated minting operations running smoothly.
- Metadata Control — Retrieve detailed metadata for collections and individual minted assets.
- Blockchain Visibility — Track the history of your digital asset distribution directly from the agent.
The Toket MCP Server exposes 8 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.
All 8 Toket tools available for LlamaIndex
When LlamaIndex connects to Toket through Vinkius, your AI agent gets direct access to every tool listed below — spanning nft-minting, web3, smart-contracts, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Provide name, symbol, and owner wallet. Create a new NFT collection
Quickly mint an NFT
Get details of a specific collection
Check Gas Tank balance
Get status of a minting transaction
List all NFT collections
List all minted NFTs
Mint an NFT into a collection
Connect Toket to LlamaIndex via MCP
Follow these steps to wire Toket into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Toket MCP Server
LlamaIndex provides unique advantages when paired with Toket through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Toket tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Toket tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Toket, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Toket tools were called, what data was returned, and how it influenced the final answer
Toket + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Toket MCP Server delivers measurable value.
Hybrid search: combine Toket real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Toket 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 Toket for fresh data
Analytical workflows: chain Toket queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Toket in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Toket immediately.
"List all NFT collections in my account."
"Mint a Founders NFT to the address '0x123...456'."
"Check the current status of my Gas Tank."
Troubleshooting Toket MCP Server with LlamaIndex
Common issues when connecting Toket to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpToket + LlamaIndex FAQ
Common questions about integrating Toket MCP Server with LlamaIndex.