LLMQuant Data

v1.0.0Finance & Fintechstable

The knowledge harness for AI‑native finance — MCP server for LLMQuant Data.

ai-agentsfinancial-datafinancial-mcpmarket-datamcp-tools
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What is LLMQuant Data?

LLMQuant Data is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to knowledge harness for ai‑native finance — mcp server for llmquant data.

The knowledge harness for AI‑native finance — MCP server for LLMQuant Data.

This server falls under the Finance & Fintech category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • The knowledge harness for AI‑native finance — MCP server for

Use Cases

Access financial market data for AI-powered trading analysis.
Integrate quantitative finance data sources with LLM agents.
LLMQuant

Maintainer

LicenseMIT
Languagetypescript
Versionv1.0.0
UpdatedMay 18, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx data

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use LLMQuant Data

LLMQuant Data MCP is a TypeScript-based MCP server that gives AI agents direct access to a comprehensive financial data platform, exposing over 16 tools covering quantitative finance research: semantic search across 50,000+ wiki entries and 1,200+ academic papers, US equity and crypto market data (OHLCV, candlestick), 50+ macroeconomic indicators from FRED, SEC filings (10-K, 10-Q, 8-K) with section extraction, institutional 13F holdings, and ETF fund data. It is designed for AI-native quantitative finance workflows where agents need structured financial context to support research and trading analysis.

Prerequisites

  • Node.js runtime (for npx-based deployment)
  • A free LLMQuant API key from llmquantdata.com (no credit card required)
  • An MCP-compatible client: Claude Desktop, Cursor, Codex CLI, or Gemini CLI
1

Obtain your LLMQuant API key

Register at llmquantdata.com to get a free API key. The free tier includes read operations and most browsing queries at 0 credits per call.

2

Add to Claude Code via CLI

Use the Claude Code CLI to register the server with your API key in a single command.

claude mcp add llmquant-data \
  -e LLMQUANT_API_KEY=your_api_key \
  -- npx -y @llmquant/data-mcp
3

Configure Claude Desktop manually

Add the server block to your Claude Desktop configuration file with the required LLMQUANT_API_KEY environment variable.

{
  "mcpServers": {
    "llmquant-data": {
      "command": "npx",
      "args": ["-y", "@llmquant/data-mcp"],
      "env": {
        "LLMQUANT_API_KEY": "your_api_key"
      }
    }
  }
}
4

Test the server with the MCP Inspector

Run the MCP Inspector to browse all 16+ available tools and execute test queries before integrating with your client.

export LLMQUANT_API_KEY=your_api_key
npx @modelcontextprotocol/inspector npx -y @llmquant/data-mcp
5

Optionally configure advanced settings

Two optional environment variables let you point to a custom API endpoint or extend the request timeout for slow network conditions.

{
  "mcpServers": {
    "llmquant-data": {
      "command": "npx",
      "args": ["-y", "@llmquant/data-mcp"],
      "env": {
        "LLMQUANT_API_KEY": "your_api_key",
        "LLMQUANT_BASE_URL": "https://api.llmquantdata.com",
        "LLMQUANT_API_TIMEOUT_MS": "30000"
      }
    }
  }
}

LLMQuant Data Examples

Client configuration

Claude Desktop config block using npx to run the LLMQuant Data MCP server with API authentication.

{
  "mcpServers": {
    "llmquant-data": {
      "command": "npx",
      "args": ["-y", "@llmquant/data-mcp"],
      "env": {
        "LLMQUANT_API_KEY": "your_api_key",
        "LLMQUANT_BASE_URL": "https://api.llmquantdata.com",
        "LLMQUANT_API_TIMEOUT_MS": "15000"
      }
    }
  }
}

Prompts to try

Example prompts to leverage LLMQuant's financial data tools from an AI assistant.

- "Search the financial wiki for articles about momentum factor investing"
- "Get daily OHLCV data for AAPL and MSFT for the past 3 months"
- "Fetch the latest 10-K filing for Tesla and extract the risk factors section"
- "Show me the most recent 13F holdings for top hedge funds"
- "What are the current values of the Fed Funds Rate and CPI from FRED?"

Troubleshooting LLMQuant Data

401 Unauthorized errors when calling tools

Verify your LLMQUANT_API_KEY is set correctly in the env block of your MCP config. Keys are case-sensitive. Generate a new key from your llmquantdata.com dashboard if needed.

Requests timing out on large data queries

Increase LLMQUANT_API_TIMEOUT_MS in your config — the maximum supported value is 120000 (120 seconds). For large date range queries, narrow the time window or request fewer tickers per call.

npx downloads the package on every startup, causing slow initialization

Install the package globally to cache it: 'npm install -g @llmquant/data-mcp', then change the command in your config to 'llmquant-data-mcp' or the globally installed binary name instead of using npx.

Frequently Asked Questions about LLMQuant Data

What is LLMQuant Data?

LLMQuant Data is a Model Context Protocol (MCP) server that knowledge harness for ai‑native finance — mcp server for llmquant data. It connects AI assistants to external tools and data sources through a standardized interface.

How do I install LLMQuant Data?

Follow the installation instructions on the LLMQuant Data GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with LLMQuant Data?

LLMQuant Data works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is LLMQuant Data free to use?

Yes, LLMQuant Data is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

Browse More Finance & Fintech MCP Servers

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Quick Config Preview

{ "mcpServers": { "data": { "command": "npx", "args": ["-y", "data"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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