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mcp-tools-cli: Deploy & Optimize Model Context Protocol Servers - MCP Implementation

mcp-tools-cli: Deploy & Optimize Model Context Protocol Servers

mcp-tools-cli: The essential command-line tool for seamlessly deploying, managing, and optimizing Model Context Protocol servers—effortlessly streamline AI workflows.

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Ranked in the top 9% of all AI tools in its category

About mcp-tools-cli

What is mcp-tools-cli: Deploy & Optimize Model Context Protocol Servers?

At its core, mcp-tools-cli is a command-line interface designed to simplify interactions with Model Context Protocol (MCP) servers. Think of it as your go-to tool for deploying, managing, and optimizing servers that host AI tools or services. Whether you're listing available tools or triggering specific functions, this CLI handles the heavy lifting by abstracting server configurations and execution details. Unlike generic tools, it’s purpose-built for MCP ecosystems, making server management a breeze.

How to use mcp-tools-cli: Deploy & Optimize Model Context Protocol Servers?

Let’s start by installing the package via pip:

pip install mcp-tools-cli

Next, configure your servers by creating a mcp_config.json file. For example, setting up a time server might look like this:

{
  "mcpServers": {
    "time": {
      "command": "python",
      "args": ["-m", "mcp_server_time", "--local-timezone=America/New_York"]
    }
  }
}

Once configured, use commands like list-tools to explore server capabilities or call-tool to execute specific functions. Here’s a quick example to list tools:

mcp-tools-cli list-tools --mcp-name time

mcp-tools-cli Features

Key Features of mcp-tools-cli: Deploy & Optimize Model Context Protocol Servers?

One standout feature is its seamless configuration handling—no manual server setup required. Simply define servers in JSON, and the CLI takes over. Another is its flexibility in passing arguments: whether JSON-formatted or simple strings, it adapts. Did we mention robust error reporting? It flags issues like missing config files or invalid commands upfront, saving you debugging time. Plus, the env field lets you inject environment variables directly into server processes.

Use cases of mcp-tools-cli: Deploy & Optimize Model Context Protocol Servers?

Imagine needing to deploy a time server to fetch localized timestamps across regions. With mcp-tools-cli, you can spin up the server in seconds and call its get_current_time

mcp-tools-cli FAQ

FAQ from mcp-tools-cli: Deploy & Optimize Model Context Protocol Servers?

Where should I place the config file?
The CLI defaults to mcp_config.json in your current directory, but you can specify a custom path using --config-path. Handy for testing different setups!

Why am I getting a JSONDecodeError?
Double-check your config syntax. Missing commas or quotes? Use a JSON validator tool to spot errors quickly.

Can I pass complex arguments to tools?
Absolutely! Use JSON strings for structured data. For example: --tool-args '{"timezone": "Asia/Tokyo"}'. The CLI even handles fallbacks for simple strings.

Content

mcp-tools-cli

This is a command-line client for interacting with Model Context Protocol (MCP) servers.

Installation

You can install mcp-tools-cli using pip:

pip install mcp-tools-cli

Configuration

The client uses a configuration file named mcp_config.json to store the connection details for MCP servers. Create a file named mcp_config.json with the following content:

{
  "mcpServers": {
    "time": {
      "command": "python",
      "args": ["-m", "mcp_server_time", "--local-timezone=America/New_York"]
    }
  }
}

Replace the values with your own MCP server configurations.

Usage

mcp-tools-cli <action> --mcp-name <mcp_name> [options]

Arguments

  • action (required): The action to perform. Must be one of:
    • list-tools: Lists the available tools on the MCP server.
    • call-tool: Calls a specific tool on the MCP server.
  • --mcp-name (required): The name of the MCP server to connect to, as defined in mcp_config.json.
  • --tool-name (required for call-tool action): The name of the tool to call.
  • --tool-args (optional): Arguments for the tool. Can be a JSON string or a single string value. If a single string value is not a valid JSON, it will be passed as the query argument to the tool.
  • --config-path (optional): Path to the mcp_config.json file. Defaults to mcp_config.json in the current directory.

Configuration

The client uses a configuration file named mcp_config.json to store the connection details for MCP servers. The file should be in the following format:

{
  "mcpServers": {
    "<mcp_name>": {
      "command": "<command to run the server>",
      "args": ["<argument1>", "<argument2>", ...],
      "env": {
        "<environment variable name>": "<environment variable value>",
        ...
      }
    },
    ...
  }
}

Replace <mcp_name> with the name of your MCP server (e.g., time). The command, args, and env fields specify how to run the server.

Examples

A sample using the Time MCP Server is provided in mcp_config.sample.json. If you want to use this, please execute pip install mcp-server-time beforehand.

  1. List available tools:
mcp-tools-cli list-tools --mcp-name time --config-path mcp_config.sample.json
  1. Call the get_current_time tool with a query:
mcp-tools-cli call-tool --mcp-name time --tool-name get_current_time --config-path mcp_config.sample.json

Error Handling

The client will print error messages to the console if any errors occur, such as:

  • FileNotFoundError: If the config file is not found.
  • json.JSONDecodeError: If the config file is not a valid JSON file.
  • ValueError: If the MCP server is not found in the config file, or if the command is missing.
  • argparse.ArgumentError: If there are invalid command-line arguments.
  • Other exceptions during tool execution.

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