How to Use the LunarCrush (Social Intelligence for Crypto Assets) MCP in LlamaIndex

Q: Can LlamaIndex store data from LunarCrush (Social Intelligence for Crypto Assets) in a vector database?

Yes. Your agent can run getmarketmetrics to retrieve trading data, format the JSON response into a Document object, and upsert it directly into your vector store for future semantic queries.

Q: How does the LunarCrush (Social Intelligence for Crypto Assets) MCP Server improve RAG accuracy in LlamaIndex?

By providing live endpoints like getaltrank, the server ensures your LlamaIndex agent bases its answers on real-time market metrics rather than outdated training data or hallucinated statistics.

Q: Can I filter which tools my LlamaIndex agent can access?

Yes, you can use the allowedtools filter during the McpToolSpec setup to expose only specific tools like getsocialmetrics while hiding others from the agent's execution list.

Index real-time crypto social metrics into LlamaIndex vector stores to ground your financial RAG applications in live market data.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect LunarCrush (Social Intelligence for Crypto Assets) MCP to LlamaIndex

Create your Vinkius account to connect LunarCrush (Social Intelligence for Crypto Assets) 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.

GDPR Free for Subscribers

Setup LunarCrush (Social Intelligence for Crypto Assets) with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build a searchable knowledge base of crypto social metrics

`get_social_metrics` fetches live engagement details that LlamaIndex instantly parses and indexes. This turns volatile social data into structured, searchable documents for your retrieval-augmented pipelines. Your agent queries this index to find patterns in historical sentiment. Instead of relying on static training data, your RAG application answers questions using fresh, indexed social metrics.

Query live market scores using an MCP Server tool spec

`get_galaxy_score` provides a real-time health indicator for any token by combining social and market data. LlamaIndex uses the MCP standard to expose this endpoint as a queryable tool for your FunctionAgent. The agent retrieves the score, updates its local index, and uses the fresh data to answer user queries. This keeps your financial agent grounded in current market reality without manual database updates.

Track and index asset rankings over time

`get_altrank` delivers a real-time performance rank based on social volume and market movement. By combining this tool with `list_assets`, LlamaIndex builds a running index of top-performing tokens. Your agent queries this local vector store to compare current rankings with past snapshots. This lets you build trend-tracking systems that evaluate shifts in social momentum over custom intervals.

Setup guide

Set up LunarCrush (Social Intelligence for Crypto Assets) 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 LunarCrush (Social Intelligence for Crypto Assets) 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 LunarCrush (Social Intelligence for Crypto Assets) tools.",
)
response = await agent.run("List recent LunarCrush (Social Intelligence for Crypto Assets) data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by LunarCrush. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect LunarCrush (Social Intelligence for Crypto Assets) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about LunarCrush (Social Intelligence for Crypto Assets) MCP in LlamaIndex

Install llama-index-tools-mcp and initialize the BasicMCPClient with the Vinkius endpoint. Convert it using McpToolSpec, then call to_tool_list_async() to register the tools with your LlamaIndex agent.

Yes. Your agent can run `get_market_metrics` to retrieve trading data, format the JSON response into a Document object, and upsert it directly into your vector store for future semantic queries.

By providing live endpoints like `get_altrank`, the server ensures your LlamaIndex agent bases its answers on real-time market metrics rather than outdated training data or hallucinated statistics.

Yes, you can use the allowed_tools filter during the McpToolSpec setup to expose only specific tools like `get_social_metrics` while hiding others from the agent's execution list.

Vinkius executes the MCP Server in an isolated sandbox. Only public market metrics and social volume data pass through the pipeline, ensuring your proprietary vector index configurations and API keys remain completely private.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript