Trade Agent MCP Server

What does “Trade Agent” MCP Server do?

The Trade Agent MCP (Model Context Protocol) Server is a remote service that enables AI agents to interact seamlessly with stock and cryptocurrency brokerages using natural-language commands. By connecting to the server, assistants can execute trades, review portfolio performance, and access real-time market data without requiring any local setup. Supporting major platforms like Charles Schwab, Robinhood, E*TRADE, Webull, Coinbase, and Kraken, Trade Agent MCP simplifies the process of trading and managing investments through secure, OAuth-based authentication. This server empowers developers and users to surface trading functionality, automate financial workflows, and gain actionable insights via AI-driven interfaces, all through a single MCP-compatible endpoint.

List of Prompts

No explicit prompt templates are mentioned in the repository or documentation.

List of Resources

No explicit resources are described in the repository or documentation.

List of Tools

• Create Trade
  Drafts a trade order for review before submission. For example: “Buy $500 of Apple” or “Sell 10 shares of SPY”.
• Execute Trade
  Executes the drafted trade order on the chosen brokerage.
• Show Account Details
  Lists linked brokerage accounts along with current value and cash balance. For example: “Show my accounts”.
• Search Asset
  Retrieves the current price and metadata for any stock or cryptocurrency. For example: “How’s Apple doing?” or “What’s the price of TSLA?”.
• Portfolio Queries (Coming Soon)
  Will allow querying portfolio performance and exposure (e.g., “How is my portfolio doing?”).
• Market Queries (Coming Soon)
  Will enable comparative market analysis (e.g., “How is Berkshire performing relative to the S&P?”).
• Copy Trading (Coming Soon)
  Will facilitate copying trades from notable portfolios (e.g., “Put $1000 in Nancy Pelosi’s portfolio.”).

Use Cases of this MCP Server

• Automated Stock and Crypto Trading
  Enables developers to implement natural-language interfaces for executing trades directly through supported brokerages, streamlining the trading process.
• Portfolio Management and Analysis
  Allows retrieval of account details and performance metrics, helping users monitor investments and cash balances across multiple brokerages.
• Market Data Retrieval
  Provides instant access to real-time prices and metadata for stocks and cryptocurrencies, facilitating informed decision-making for both AI agents and users.
• Brokerage Aggregation
  Consolidates multiple brokerage accounts under a single interface, making it easier to manage diverse portfolios and assets.
• Planned Advanced Analytics
  Upcoming tools such as portfolio and market queries, as well as copy trading, will enable deeper insights and automation in investment strategies.

How to set it up

Windsurf

1. Ensure you have Node.js installed on your machine.
2. Locate your Windsurf configuration file.
3. Add the Trade Agent MCP Server to your mcpServers object.
4. Save the configuration and restart Windsurf.
5. Verify that the MCP server is accessible.

Example JSON:

{
  "mcpServers": {
    "trade-agent": {
      "command": "npx",
      "args": ["@Trade-Agent/trade-agent-mcp@latest"]
    }
  }
}

Securing API Keys:

{
  "mcpServers": {
    "trade-agent": {
      "command": "npx",
      "args": ["@Trade-Agent/trade-agent-mcp@latest"],
      "env": {
        "TRADE_AGENT_API_KEY": "${TRADE_AGENT_API_KEY}"
      },
      "inputs": {
        "apiKey": "${TRADE_AGENT_API_KEY}"
      }
    }
  }
}

Claude

1. Make sure Node.js is installed.
2. Open your Claude configuration file.
3. Insert the Trade Agent MCP Server details.
4. Save changes and restart Claude.
5. Confirm the connection.

Example JSON:

{
  "mcpServers": {
    "trade-agent": {
      "command": "npx",
      "args": ["@Trade-Agent/trade-agent-mcp@latest"]
    }
  }
}

Securing API Keys:

{
  "mcpServers": {
    "trade-agent": {
      "command": "npx",
      "args": ["@Trade-Agent/trade-agent-mcp@latest"],
      "env": {
        "TRADE_AGENT_API_KEY": "${TRADE_AGENT_API_KEY}"
      },
      "inputs": {
        "apiKey": "${TRADE_AGENT_API_KEY}"
      }
    }
  }
}

Cursor

1. Install Node.js if not already present.
2. Locate the Cursor configuration settings.
3. Add the Trade Agent MCP Server configuration.
4. Save and restart Cursor.
5. Test the MCP connection.

Example JSON:

{
  "mcpServers": {
    "trade-agent": {
      "command": "npx",
      "args": ["@Trade-Agent/trade-agent-mcp@latest"]
    }
  }
}

Securing API Keys:

{
  "mcpServers": {
    "trade-agent": {
      "command": "npx",
      "args": ["@Trade-Agent/trade-agent-mcp@latest"],
      "env": {
        "TRADE_AGENT_API_KEY": "${TRADE_AGENT_API_KEY}"
      },
      "inputs": {
        "apiKey": "${TRADE_AGENT_API_KEY}"
      }
    }
  }
}

Cline

1. Verify Node.js is installed on your system.
2. Open the Cline configuration file.
3. Add the Trade Agent MCP Server under mcpServers.
4. Save and restart Cline.
5. Confirm proper setup.

Example JSON:

{
  "mcpServers": {
    "trade-agent": {
      "command": "npx",
      "args": ["@Trade-Agent/trade-agent-mcp@latest"]
    }
  }
}

Securing API Keys:

{
  "mcpServers": {
    "trade-agent": {
      "command": "npx",
      "args": ["@Trade-Agent/trade-agent-mcp@latest"],
      "env": {
        "TRADE_AGENT_API_KEY": "${TRADE_AGENT_API_KEY}"
      },
      "inputs": {
        "apiKey": "${TRADE_AGENT_API_KEY}"
      }
    }
  }
}

How to use this MCP inside flows

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:

{
  "trade-agent": {
    "transport": "streamable_http",
    "url": "https://mcp.thetradeagent.ai/sse"
  }
}

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 “trade-agent” to whatever the actual name of your MCP server is if you wish, and replace the URL with your own MCP server URL if self-hosting.

Overview

Overall, the Trade Agent MCP server provides a solid toolset for trading and account management, but lacks explicit prompt templates and resource definitions. Documentation is clear and practical, yet the absence of advanced MCP features (roots, sampling, resources) means it is best for straightforward trading use cases.

MCP Score

Rating:
Based on the above tables, I would rate the Trade Agent MCP server a 5/10 for overall MCP maturity and completeness. It is functional and well-documented for its main use case, but lacks some standard MCP elements like prompt templates and resource exposure, and does not mention advanced features like roots or sampling.