MCP JSON Configuration 🤝 FastMCP

FastMCP can generate standard MCP JSON configuration files that work with any MCP-compatible client including Claude Desktop, VS Code, Cursor, and other applications that support the Model Context Protocol.

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MCP JSON Configuration Standard

The MCP JSON configuration format is an emergent standard that has developed across the MCP ecosystem. This format defines how MCP clients should configure and launch MCP servers, providing a consistent way to specify server commands, arguments, and environment variables.

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Configuration Structure

The standard uses a mcpServers object where each key represents a server name and the value contains the server’s configuration:

{
  "mcpServers": {
    "server-name": {
      "command": "executable",
      "args": ["arg1", "arg2"],
      "env": {
        "VAR": "value"
      }
    }
  }
}

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Server Configuration Fields

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command (required)

The executable command to run the MCP server. This should be an absolute path or a command available in the system PATH.

{
  "command": "python"
}

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args (optional)

An array of command-line arguments passed to the server executable. Arguments are passed in order.

{
  "args": ["server.py", "--verbose", "--port", "8080"]
}

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env (optional)

An object containing environment variables to set when launching the server. All values must be strings.

{
  "env": {
    "API_KEY": "secret-key",
    "DEBUG": "true",
    "PORT": "8080"
  }
}

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Client Adoption

This format is widely adopted across the MCP ecosystem:

• Claude Desktop: Uses ~/.claude/claude_desktop_config.json
• Cursor: Uses ~/.cursor/mcp.json
• VS Code: Uses workspace .vscode/mcp.json
• Other clients: Many MCP-compatible applications follow this standard

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Overview

The fastmcp install mcp-json command generates configuration in the standard mcpServers format used across the MCP ecosystem. This is useful when:

• Working with unsupported clients - Any MCP client not directly integrated with FastMCP
• CI/CD environments - Automated configuration generation for deployments
• Configuration sharing - Easy distribution of server setups to team members
• Custom tooling - Integration with your own MCP management tools
• Manual setup - When you prefer to manually configure your MCP client

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Basic Usage

Generate configuration and output to stdout (useful for piping):

fastmcp install mcp-json server.py

This outputs the server configuration JSON that you add to the mcpServers object:

{
  "command": "uv",
  "args": [
    "run",
    "--with",
    "fastmcp", 
    "fastmcp",
    "run",
    "/absolute/path/to/server.py"
  ]
}

To use this in a client configuration file, add it under a server name in the mcpServers object:

{
  "mcpServers": {
    "My Server": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "fastmcp", 
        "fastmcp",
        "run",
        "/absolute/path/to/server.py"
      ]
    }
  }
}

​

Configuration Options

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Server Naming

# Use server's built-in name (from FastMCP constructor)
fastmcp install mcp-json server.py

# Override with custom name
fastmcp install mcp-json server.py --name "Custom Server Name"

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Dependencies

Add Python packages your server needs:

# Single package
fastmcp install mcp-json server.py --with pandas

# Multiple packages  
fastmcp install mcp-json server.py --with pandas --with requests --with httpx

# Editable local package
fastmcp install mcp-json server.py --with-editable ./my-package

You can also specify dependencies directly in your server code:

from fastmcp import FastMCP

mcp = FastMCP(
    name="Data Analysis Server",
    dependencies=["pandas", "matplotlib", "seaborn"]
)

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Environment Variables

# Individual environment variables
fastmcp install mcp-json server.py \
  --env-var API_KEY=your-secret-key \
  --env-var DEBUG=true

# Load from .env file
fastmcp install mcp-json server.py --env-file .env

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Server Object Selection

Use the same file.py:object notation as other FastMCP commands:

# Auto-detects server object (looks for 'mcp', 'server', or 'app')
fastmcp install mcp-json server.py

# Explicit server object
fastmcp install mcp-json server.py:my_custom_server

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Clipboard Integration

Copy configuration directly to your clipboard for easy pasting:

fastmcp install mcp-json server.py --copy

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Usage Examples

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Basic Server

fastmcp install mcp-json dice_server.py

Output:

{
  "command": "uv",
  "args": [
    "run",
    "--with",
    "fastmcp",
    "fastmcp", 
    "run",
    "/home/user/dice_server.py"
  ]
}

​

Production Server with Dependencies

fastmcp install mcp-json api_server.py \
  --name "Production API Server" \
  --with requests \
  --with python-dotenv \
  --env-var API_BASE_URL=https://api.example.com \
  --env-var TIMEOUT=30

Output:

{
  "command": "uv",
  "args": [
    "run",
    "--with",
    "fastmcp",
    "--with",
    "python-dotenv", 
    "--with",
    "requests",
    "fastmcp",
    "run", 
    "/home/user/api_server.py"
  ],
  "env": {
    "API_BASE_URL": "https://api.example.com",
    "TIMEOUT": "30"
  }
}

​

Pipeline Usage

Save configuration to file:

fastmcp install mcp-json server.py > mcp-config.json

Use in shell scripts:

#!/bin/bash
CONFIG=$(fastmcp install mcp-json server.py --name "CI Server")
echo "$CONFIG" | jq '.command'
# Output: "uv"

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Integration with MCP Clients

The generated configuration works with any MCP-compatible application:

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Claude Desktop

Copy the mcpServers object into ~/.claude/claude_desktop_config.json

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Cursor

Add to ~/.cursor/mcp.json

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VS Code

Add to your workspace’s .vscode/mcp.json file

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Custom Applications

Use the JSON configuration with any application that supports the MCP protocol

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Configuration Format

The generated configuration follows the standard MCP server specification:

{
  "mcpServers": {
    "<server-name>": {
      "command": "<executable>",
      "args": ["<arg1>", "<arg2>", "..."],
      "env": {
        "<ENV_VAR>": "<value>"
      }
    }
  }
}

Fields:

• command: The executable to run (always uv for FastMCP servers)
• args: Command-line arguments including dependencies and server path
• env: Environment variables (only included if specified)

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Requirements

• uv: Must be installed and available in your system PATH
• pyperclip (optional): Required only for --copy functionality

Install uv if not already available:

# macOS
brew install uv

# Linux/Windows  
curl -LsSf https://astral.sh/uv/install.sh | sh