
Nasdaq Data Link MCP Server
Integrate real-time and historical financial data into your AI workflows with the Nasdaq Data Link MCP Server. Seamlessly connect AI assistants to the Nasdaq Da...
Connect your AI agents to powerful financial data APIs—retrieve stock prices, analyze statements, pull crypto data, and automate finance insights with the Financial Datasets MCP Server.
The Financial Datasets MCP Server is a Model Context Protocol (MCP) server designed to provide seamless access to comprehensive stock market data from the Financial Datasets API. By acting as a bridge between AI assistants (such as Claude) and external financial data sources, this server enables AI-powered workflows to retrieve up-to-date financial information effortlessly. Developers and AI agents can use it to query income statements, balance sheets, cash flow statements, current and historical stock prices, as well as market news for publicly traded companies. The server also supports cryptocurrency price lookups and news retrieval. This integration streamlines the process of financial data collection and analysis within AI-driven development environments, empowering users to build sophisticated financial tools and insights with minimal manual effort.
No explicit prompt templates are mentioned in the repository or documentation.
No explicit MCP resources are listed in the repository or documentation.
No Windsurf-specific instructions are provided in the repository.
mkdir -p ~/Library/Application\ Support/Claude/
nano ~/Library/Application\ Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"financial-datasets": {
"command": "/path/to/uv",
"args": [
"--directory",
"/absolute/path/to/financial-datasets-mcp",
"run",
"server.py"
]
}
}
}
/path/to/uv
with the output of which uv
and /absolute/path/to/financial-datasets-mcp
with the full path to the cloned repository.Set up your .env
file as follows:
FINANCIAL_DATASETS_API_KEY=your-financial-datasets-api-key
No explicit JSON env example is given, but use environment variables as shown.
No Cursor-specific instructions are provided in the repository.
No Cline-specific instructions are provided in the repository.
Using MCP in FlowHunt
To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:
Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:
{
"financial-datasets": {
"transport": "streamable_http",
"url": "https://yourmcpserver.example/pathtothemcp/url"
}
}
Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “financial-datasets” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.
Section | Availability | Details/Notes |
---|---|---|
Overview | ✅ | Overview provided in README.md |
List of Prompts | ⛔ | No prompt templates mentioned |
List of Resources | ⛔ | No explicit MCP resources listed |
List of Tools | ✅ | 10 tools listed in README.md and server.py |
Securing API Keys | ✅ | .env usage described; API key environment variable required |
Sampling Support (less important in evaluation) | ⛔ | Not mentioned |
Between these two tables, the Financial Datasets MCP Server is a focused, well-documented, and highly practical integration for financial data retrieval, but lacks explicit prompt, resource, and advanced MCP feature documentation. Rating: 7/10.
Has a LICENSE | ✅ (MIT) |
---|---|
Has at least one tool | ✅ |
Number of Forks | 69 |
Number of Stars | 357 |
It's a Model Context Protocol (MCP) server connecting AI agents to comprehensive, up-to-date financial and cryptocurrency data—enabling automated access to statements, prices, and news for public companies and crypto assets.
You can retrieve income statements, balance sheets, cash flow statements, current and historical stock prices, company news, as well as cryptocurrency tickers and historical/current prices.
Automate financial statement analysis, monitor stock and crypto prices, integrate market news into chatbots, and build multi-asset dashboards or trading tools.
Store your FINANCIAL_DATASETS_API_KEY in a `.env` file. Do not hard-code sensitive credentials in your configuration files.
Yes! Add the MCP component to your flow, configure it with your MCP server details, and your AI agent can access all financial data tools seamlessly.
Empower your AI workflows with seamless, real-time access to financial and crypto data using the Financial Datasets MCP Server. Start building smarter finance tools today.
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