Finnhub MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Finnhub as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Finnhub. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in Finnhub?"
)
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 Finnhub MCP Server
Empower your AI agent to orchestrate your entire financial research and market auditing workflow with Finnhub, the comprehensive platform for real-time stock and crypto data. By connecting Finnhub to your agent, you transform complex market querying into a natural conversation. Your agent can instantly retrieve stock quotes, audit company profiles, and monitor market news without you ever touching a financial terminal. Whether you are conducting investment research or tracking crypto trends, your agent acts as a real-time financial analyst, ensuring your intelligence is always grounded in live market data.
LlamaIndex agents combine Finnhub tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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
- Stock Auditing — Retrieve real-time price quotes for thousands of global stocks and maintain a clear view of market changes.
- Company Oversight — Audit comprehensive company profiles and basic financial metrics to understand organizational health.
- Market Intelligence — Search for stock and crypto symbols to identify relevant assets for your portfolio instantly.
- News Discovery — Monitor latest market news across various categories, including general, forex, and crypto, to stay on top of trends.
- Crypto Monitoring — List supported crypto symbols for dozens of exchanges to maintain strict control over digital asset data.
The Finnhub MCP Server exposes 6 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 Finnhub to LlamaIndex via MCP
Follow these steps to integrate the Finnhub 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 6 tools from Finnhub
Why Use LlamaIndex with the Finnhub MCP Server
LlamaIndex provides unique advantages when paired with Finnhub through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Finnhub tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Finnhub tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Finnhub, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Finnhub tools were called, what data was returned, and how it influenced the final answer
Finnhub + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Finnhub MCP Server delivers measurable value.
Hybrid search: combine Finnhub real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Finnhub 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 Finnhub for fresh data
Analytical workflows: chain Finnhub queries with LlamaIndex's data connectors to build multi-source analytical reports
Finnhub MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect Finnhub to LlamaIndex via MCP:
get_basic_financials
Get basic financial metrics for a company
get_company_profile
Get general information about a company by symbol
get_market_news
Get latest market news in a category
get_stock_quote
Get real-time quote data for a specific stock symbol
list_crypto_symbols
List supported crypto symbols for an exchange
search_symbols
Search for stock or crypto symbols by name
Example Prompts for Finnhub in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Finnhub immediately.
"Get the current stock quote for 'AAPL' (Apple) using Finnhub."
"Show the latest news in the 'crypto' category."
"What are the basic financial metrics for 'MSFT' (Microsoft)?"
Troubleshooting Finnhub MCP Server with LlamaIndex
Common issues when connecting Finnhub to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFinnhub + LlamaIndex FAQ
Common questions about integrating Finnhub 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 Finnhub with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
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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 Finnhub to LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.