How to Use the Meld MCP in LlamaIndex

Q: How do I connect the Meld MCP server to LlamaIndex?

Install llama-index-tools-mcp and instantiate the basic MCP client with the server endpoint. Convert the client tools using totoollistasync() and pass them to your LlamaIndex agent.

Q: Can LlamaIndex query Meld tools during a RAG pipeline?

Yes, your agent dynamically decides to call getexchangerates or getnetwork to resolve specific user queries. The retrieved data is injected directly into the LLM's context window.

Q: How does LlamaIndex handle rate limits when polling Meld?

Implement a local caching layer for frequent calls like getexchangerates to prevent your RAG application from triggering rate limits during high-frequency user queries.

Index multi-chain wallet data and transaction histories into LlamaIndex for grounded, hallucination-free financial RAG.

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Connect Meld MCP to LlamaIndex

Create your Vinkius account to connect Meld to LlamaIndex 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 Meld with LlamaIndex

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Index live transactions with this MCP Server.

This LlamaIndex connector maps the Meld financial API directly to your knowledge indexes for real-time data retrieval. This MCP Server lets your indexer call `list_transactions` to pull recent blockchain activity directly into your local vector database. Instead of guessing, your financial RAG pipeline queries actual on-chain records. This grounds your answers in verified ledger events rather than relying on the LLM's static training data.

Build a searchable knowledge base of digital assets.

The Meld asset catalog tools feed up-to-date token metadata directly into your LlamaIndex vector store. Your indexing pipeline uses `list_assets` and `search_assets` to discover new tokens and index their metadata automatically. By storing these details in a searchable index, your application instantly resolves queries about token contracts or supply metrics. This makes your financial search engine incredibly accurate.

Ground wallet queries in real-time balance data.

The Meld wallet query tools provide live balance data to eliminate hallucinations in LlamaIndex applications. By exposing `get_wallet_details` and `get_account_info` as tools, your agent pulls live balances before generating any financial summary. This setup ensures accuracy when users ask about their holdings. The agent fetches the exact balance, writes it to the query context, and references it directly in the final response.

Setup guide

Set up Meld MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Meld MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Meld tools.",
)
response = await agent.run("List recent Meld data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Meld. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Meld MCP in LlamaIndex

Install `llama-index-tools-mcp` and instantiate the basic MCP client with the server endpoint. Convert the client tools using `to_tool_list_async()` and pass them to your LlamaIndex agent.

Yes, your agent dynamically decides to call `get_exchange_rates` or `get_network` to resolve specific user queries. The retrieved data is injected directly into the LLM's context window.

Implement a local caching layer for frequent calls like `get_exchange_rates` to prevent your RAG application from triggering rate limits during high-frequency user queries.

Yes, filter the tool list before passing it to the agent. If you only want to allow balance checks, expose just `get_wallet_details` and hide the rest.

Your account info and wallet details never touch third-party indexing servers. Vinkius executes the MCP server in a secure sandbox, and all financial data flows directly to your local LlamaIndex instance.

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