FastMCP
A collection of MCP servers providing utilities including user greeting, message decoding, text file reading with PDF summary generation, and NASA-quality code auditing using a trained AI model to predict software defects and measure code complexity.
What is FastMCP?
FastMCP is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to collection of mcp servers providing utilities including user greeting, message decoding, text file reading with pdf summary generation, and nasa-quality code auditing using a trained ai model to predi...
A collection of MCP servers providing utilities including user greeting, message decoding, text file reading with PDF summary generation, and NASA-quality code auditing using a trained AI model to predict software defects and measure code complexity.
This server falls under the Developer Tools category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- A collection of MCP servers providing utilities including us
Use Cases
Maintainer
Works with
Installation
NPM
npx -y fastmcpManual Installation
npx -y fastmcpConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use FastMCP
FastMCP (rutie345/FastMCP) is a collection of Python-based MCP servers built with the FastMCP framework that demonstrates how to expose custom tools to AI assistants via the Model Context Protocol. The collection includes four servers: a user greeting server, a message decoder (reverses letter order), a text file reader with AI-powered PDF summary generation, and a NASA-Quality Auditor that uses a trained defect prediction model to score code bug probability and measure complexity. It is designed for developers learning to build MCP servers with Python and for users who want quick code quality auditing or document summarization through an AI assistant like Claude via the Cline VS Code extension.
Prerequisites
- Python 3.10 or later installed
- pip or uv package manager available
- The FastMCP Python library installed ('pip install fastmcp')
- VS Code with the Cline extension installed (for the documented integration path)
- Optional: an AI API key (Anthropic or compatible) configured in Cline for PDF summarization
Clone the FastMCP server collection
Clone the repository to get the four example MCP server scripts.
git clone https://github.com/rutie345/FastMCP
cd FastMCPCreate a Python virtual environment and install dependencies
Set up an isolated Python environment and install the FastMCP library.
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install fastmcpConfigure the servers in Cline (VS Code)
In VS Code, open the Cline extension, click the database icon to open MCP server settings, navigate to 'Remote Servers' then 'Edit Configuration', and add JSON entries pointing to each server script using the virtual environment's Python executable.
{
"mcpServers": {
"ChatAOS": {
"command": "/path/to/FastMCP/venv/bin/python",
"args": ["/path/to/FastMCP/fast_mcp_ex_1.py"]
},
"ChatAOS2": {
"command": "/path/to/FastMCP/venv/bin/python",
"args": ["/path/to/FastMCP/fast_mcp_ex_2.py"]
},
"TextSintetizer": {
"command": "/path/to/FastMCP/venv/bin/python",
"args": ["/path/to/FastMCP/fast_mcp_ex_3.py"]
},
"NASA-Quality-Auditor": {
"command": "/path/to/FastMCP/venv/bin/python",
"args": ["/path/to/FastMCP/fast_mcp_ex_4.py"]
}
}
}Verify servers show green status in Cline
In the Cline MCP server panel, each configured server should show a green indicator when running correctly. If any show red, check the Python path and script path are correct.
Use the servers from within Cline or Claude
With servers active, you can prompt Claude (via Cline) to use the tools: greet a user, decode a message, summarize a file, or audit code quality.
FastMCP Examples
Client configuration
MCP server configuration for all four FastMCP servers using local Python venv paths.
{
"mcpServers": {
"ChatAOS": {
"command": "/path/to/FastMCP/venv/bin/python",
"args": ["/path/to/FastMCP/fast_mcp_ex_1.py"]
},
"NASA-Quality-Auditor": {
"command": "/path/to/FastMCP/venv/bin/python",
"args": ["/path/to/FastMCP/fast_mcp_ex_4.py"]
}
}
}Prompts to try
Example prompts to use once the FastMCP servers are running in Cline.
- "Use the ChatAOS server to greet the user Alice"
- "Use ChatAOS2 to decode the message 'dlrow olleh'"
- "Use TextSintetizer to read report.txt and generate a PDF summary"
- "Use the NASA-Quality-Auditor to analyze main.py and give me a bug probability score"
- "Run a code complexity assessment on the entire src/ directory"Troubleshooting FastMCP
Server shows red status in Cline with 'module not found: fastmcp'
The Cline config must use the Python executable inside your virtual environment (e.g. /path/to/FastMCP/venv/bin/python), not the system Python. Run 'which python' inside the activated venv to get the correct path.
NASA-Quality-Auditor returns an error analyzing large files
The defect prediction model may have file size or complexity limits. Try passing individual functions or smaller code snippets rather than entire files. Ensure the trained model artifact is present in the repository directory.
TextSintetizer fails to generate a PDF
PDF generation likely requires additional Python libraries (such as reportlab or fpdf2). Check the script's imports and install any missing dependencies with 'pip install reportlab' inside your virtual environment.
Frequently Asked Questions about FastMCP
What is FastMCP?
FastMCP is a Model Context Protocol (MCP) server that collection of mcp servers providing utilities including user greeting, message decoding, text file reading with pdf summary generation, and nasa-quality code auditing using a trained ai model to predict software defects and measure code complexity. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install FastMCP?
Install via npm with the command: npx -y fastmcp. Then add the server configuration to your AI client's JSON config file (e.g., claude_desktop_config.json or .cursor/mcp.json).
Which AI clients work with FastMCP?
FastMCP works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is FastMCP free to use?
Yes, FastMCP is open source and available under the Apache-2.0 license. You can use it freely in both personal and commercial projects.
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Quick Config Preview
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