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MCP Agents

by amajakai14
GitHub
Python
MIT License
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MCP Agents 🚀

FastMCP-based Model Context Protocol servers providing various tools, resources, and prompts for AI assistants.

Quick Start with uvx

The easiest way to run these MCP servers is using uvx (recommended):

# Run the default basic server uvx @amajakai14/mcp-agents # Or run specific servers uvx @amajakai14/mcp-agents --script mcp-basic-server uvx @amajakai14/mcp-agents --script mcp-advanced-server

What is MCP?

The Model Context Protocol (MCP) is a standardized way to connect LLMs to tools and data. It provides:

  • Tools: Functions that LLMs can call to perform actions (like API endpoints)

  • Resources: Data that can be loaded into LLM context

  • Prompts: Reusable templates for LLM interactions

Installation Options

Option 1: Using uvx (Recommended)

# Install uvx if you haven't already pip install uvx # Run the default server uvx @amajakai14/mcp-agents # Or run specific servers uvx @amajakai14/mcp-agents --script mcp-basic-server uvx @amajakai14/mcp-agents --script mcp-advanced-server

Option 2: Clone and Run Locally

# Clone the repository git clone https://github.com/amajakai14/mcp-agents.git cd mcp-agents # Install dependencies pip3 install -r requirements.txt # Run the servers python3 basic_mcp_server.py python3 advanced_mcp_server.py

Option 3: Install from PyPI (Future)

pip install mcp-agents mcp-agents # Run default server mcp-basic-server # Run basic server mcp-advanced-server # Run advanced server

Running the Servers

Publishing to PyPI

To publish this package to PyPI so users can use uvx @amajakai14/mcp-agents:

  1. Build the package:

    pip install build twine python -m build

  2. Upload to PyPI:

    twine upload dist/*

  3. Or use GitHub Actions: Create a release on GitHub and the workflow will automatically publish to PyPI.

Testing Your MCP Server

  1. Run the basic server:

    python3 basic_mcp_server.py

  2. Run the advanced server:

    python3 advanced_mcp_server.py

Available Servers

Basic MCP Server (basic_mcp_server.py)

A simple server demonstrating fundamental MCP tools:

  • add_numbers(a, b) - Add two numbers

  • multiply_numbers(a, b) - Multiply two numbers

  • get_current_time() - Get current timestamp

  • create_file_content(filename, content) - Create a file

  • list_files_in_directory(directory) - List directory contents

  • calculate_factorial(n) - Calculate factorial

  • format_json(data) - Format JSON with indentation

  • word_count(text) - Count words, characters, and lines

Advanced MCP Server (advanced_mcp_server.py)

A comprehensive server showing tools, resources, and prompts:

Tools:

  • add_note(title, content, tags) - Add a note

  • search_notes(query) - Search through notes

  • add_todo(task, priority) - Add a todo item

  • complete_todo(todo_id) - Mark todo as completed

  • create_database_table(table_name, columns) - Create SQLite table

Resources:

  • notes://all - Get all notes as formatted text

  • todos://pending - Get pending todo items

  • system://stats - Get system statistics

Prompts:

  • note_summarizer(note_ids) - Generate note summary prompt

  • task_prioritizer() - Generate task prioritization prompt

Using with LLM Applications

Claude Desktop

Add this to your Claude Desktop configuration:

Claude Desktop

Add this to your Claude Desktop configuration:

Simple Configuration (Default - Basic Server):

{ "mcpServers": { "mcp-agents": { "command": "uvx", "args": ["@amajakai14/mcp-agents"] } } }

Multiple Servers Configuration:

{ "mcpServers": { "mcp-basic": { "command": "uvx", "args": ["@amajakai14/mcp-agents", "--script", "mcp-basic-server"] }, "mcp-advanced": { "command": "uvx", "args": ["@amajakai14/mcp-agents", "--script", "mcp-advanced-server"] } } }

For local installation:

{ "mcpServers": { "mcp-agents": { "command": "python3", "args": ["/path/to/your/advanced_mcp_server.py"], "env": {} } } }

Other MCP Clients

See client_example.py for programmatic usage examples.

Creating Your Own MCP Tools

Here's the basic pattern for creating MCP tools with FastMCP:

from fastmcp import FastMCP # Create server instance mcp = FastMCP("My Server") # Add a tool (function LLMs can call) @mcp.tool def my_tool(param1: str, param2: int) -> str: """Description of what this tool does.""" return f"Processed {param1} with {param2}" # Add a resource (data LLMs can access) @mcp.resource("data://my-resource") def my_resource() -> str: """Get some data.""" return "This is my resource data" # Add a prompt template @mcp.prompt def my_prompt(context: str) -> str: """Generate a prompt template.""" return f"Please analyze this: {context}" # Run the server if __name__ == "__main__": mcp.run()

Key Concepts

Tools vs Resources vs Prompts

  • Tools: Use @mcp.tool for functions that do something (create, update, calculate, etc.)

  • Resources: Use @mcp.resource("uri") for functions that provide data (read, fetch, list, etc.)

  • Prompts: Use @mcp.prompt for functions that generate prompt templates

Type Hints

Always use type hints - FastMCP uses them to generate proper schemas:

@mcp.tool def my_tool(text: str, count: int = 1) -> List[str]: """Tool with proper type hints.""" return [text] * count

Error Handling

Handle errors gracefully in your tools:

@mcp.tool def safe_tool(data: str) -> Dict[str, Any]: """A tool with proper error handling.""" try: result = process_data(data) return {"status": "success", "result": result} except Exception as e: return {"status": "error", "message": str(e)}

Deployment

Local Development

python your_server.py

FastMCP Cloud (Free)

Deploy to FastMCP Cloud for free hosting.

Custom Infrastructure

Use the built-in FastMCP deployment tools for your own servers.

Learn More

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Provides FastMCP-based servers with various tools for AI assistants including math operations, file management, note-taking, todo management, and database operations. Offers both basic and advanced server configurations with tools, resources, and prompt templates.

  1. Quick Start with uvx
    1. What is MCP?
      1. Installation Options
        1. Option 1: Using uvx (Recommended)
        2. Option 2: Clone and Run Locally
        3. Option 3: Install from PyPI (Future)
        4. Running the Servers
      2. Publishing to PyPI
        1. Testing Your MCP Server
          1. Available Servers
            1. Basic MCP Server (basic_mcp_server.py)
            2. Advanced MCP Server (advanced_mcp_server.py)
          2. Using with LLM Applications
            1. Claude Desktop
            2. Claude Desktop
            3. Other MCP Clients
          3. Creating Your Own MCP Tools
            1. Key Concepts
              1. Tools vs Resources vs Prompts
              2. Type Hints
              3. Error Handling
            2. Deployment
              1. Local Development
              2. FastMCP Cloud (Free)
              3. Custom Infrastructure
            3. Learn More

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