mcp-name: io.github.MusaddiqueHussainLabs/mhlabs_mcp_tools

🧠 mhlabs-mcp-tools

mhlabs-mcp-tools is a Modular MCP Tools Server built using FastMCP.
It provides an extendable AI tool ecosystem organized into functional categories (Text Preprocessing, NLP Components, Document Analysis, etc.) that can be dynamically loaded and served through MCP (Model Context Protocol) via STDIO transport.

This project is part of the MHLabs AI Agentic Ecosystem, designed to work with mhlabs-mcp-server, mhlabs-mcp-agents, and downstream A2A agent frameworks.

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Features

• FastMCP Server: Pure FastMCP implementation supporting multiple transport protocols
• Factory Pattern: Reusable MCP tools factory for easy service management
• Domain-Based Organization: Services organized by business domains (HR, Tech Support, etc.)
• Authentication: Optional Azure AD authentication support
• Multiple Transports: STDIO, HTTP (Streamable), and SSE transport support
• VS Code Integration: Debug configurations and development settings
• Comprehensive Testing: Unit tests with pytest
• Flexible Configuration: Environment-based configuration management

Architecture

mhlabs_mcp_tools/
├── .gitignore
├── .vscode/
│   └── settings.json
├── CHANGELOG.md
├── LICENSE
├── README.md
├── docs/
│   └── index.md
├── examples/
│   ├── example_client.py
│   └── example_client_http.py
├── mkdocs.yml
├── pyproject.toml
├── requirements.txt
├── server.json
└── src/
    ├── __init__.py
    ├── main.py
    └── mhlabs_mcp_tools/
        ├── __init__.py
        ├── core/
        │   ├── __init__.py
        │   ├── config.py
        │   ├── constants.py
        │   ├── factory.py
        │   └── prompts.py
        ├── data/
        │   ├── __init__.py
        │   ├── external/
        │   │   └── __init__.py
        │   ├── interim/
        │   │   └── __init__.py
        │   ├── processed/
        │   │   └── __init__.py
        │   └── raw/
        │       ├── __init__.py
        │       ├── contractions_dict.json
        │       ├── custom_substitutions.csv
        │       ├── leftovers_dict.json
        │       └── slang_dict.json
        ├── handlers/
        │   ├── __init__.py
        │   ├── custom_exceptions.py
        │   └── output_generator.py
        ├── mcp_server.py
        ├── models/
        │   └── __init__.py
        ├── nlp_components/
        │   ├── __init__.py
        │   └── nlp_model.py
        ├── services/
        │   ├── __init__.py
        │   ├── langchain_framework.py
        │   └── spacy_extractor.py
        └── text_preprocessing/
            ├── __init__.py
            ├── contractions.py
            ├── emo_unicode.py
            ├── slang_text.py
            └── text_preprocessing.py

Available Services

Currently the package is organized into three primary modules:

1. NLP Components

Component Type	Description
tokenize	Text tokenization
pos	Part-of-Speech tagging
lemma	Word lemmatization
morphology	Study of word forms
dep	Dependency parsing
ner	Named Entity Recognition
norm	Text normalization

2. Text Preprocessing

This module equips users with an extensive set of text preprocessing tools:

Function	Description
to_lower	Convert text to lowercase
to_upper	Convert text to uppercase
remove_number	Remove numerical characters
remove_itemized_bullet_and_numbering	Eliminate itemized/bullet-point numbering
remove_url	Remove URLs from text
remove_punctuation	Remove punctuation marks
remove_special_character	Remove special characters
keep_alpha_numeric	Keep only alphanumeric characters
remove_whitespace	Remove excess whitespace
normalize_unicode	Normalize Unicode characters
remove_stopword	Eliminate common stopwords
remove_freqwords	Remove frequently occurring words
remove_rarewords	Remove rare words
remove_email	Remove email addresses
remove_phone_number	Remove phone numbers
remove_ssn	Remove Social Security Numbers (SSN)
remove_credit_card_number	Remove credit card numbers
remove_emoji	Remove emojis
remove_emoticons	Remove emoticons
convert_emoticons_to_words	Convert emoticons to words
convert_emojis_to_words	Convert emojis to words
remove_html	Remove HTML tags
chat_words_conversion	Convert chat language to standard English
expand_contraction	Expand contractions (e.g., "can't" to "cannot")
tokenize_word	Tokenize words
tokenize_sentence	Tokenize sentences
stem_word	Stem words
lemmatize_word	Lemmatize words
preprocess_text	Combine multiple preprocessing steps into one function

Quick Start

Development Setup

1. Clone and Navigate:

   cd src/mhlabs_mcp_tools
   

2. Install Dependencies:

   pip install -r requirements.txt
   

3. Configure Environment:

   cp .env.example .env
   # Edit .env with your configuration
   

4. Start the Server:

   # Default STDIO transport (for local MCP clients)
   python mcp_server.py
   
   # HTTP transport (for web-based clients)
   python mcp_server.py --transport http --port 9000
   or
   after installed mhlabs-mcp-tools
   python -m mhlabs_mcp_tools.mcp_server --transport http --port 9000
   
   # Using FastMCP CLI (recommended)
   fastmcp run mcp_server.py -t streamable-http --port 9000 -l DEBUG
   
   # Debug mode with authentication disabled
   python mcp_server.py --transport http --debug --no-auth
   

Transport Options

1. STDIO Transport (default)

• 🔧 Perfect for: Local tools, command-line integrations, Claude Desktop
• 🚀 Usage: python mcp_server.py or python mcp_server.py --transport stdio

2. HTTP (Streamable) Transport

• 🌐 Perfect for: Web-based deployments, microservices, remote access
• 🚀 Usage: python mcp_server.py --transport http --port 9000
• 🌐 URL: http://127.0.0.1:9000/mcp/

3. SSE Transport (deprecated)

• ⚠️ Legacy support only - use HTTP transport for new projects
• 🚀 Usage: python mcp_server.py --transport sse --port 9000

FastMCP CLI Usage

# Standard HTTP server
fastmcp run mcp_server.py -t streamable-http --port 9000 -l DEBUG

# With custom host
fastmcp run mcp_server.py -t streamable-http --host 0.0.0.0 --port 9000 -l DEBUG

# STDIO transport (for local clients)
fastmcp run mcp_server.py -t stdio

# Development mode with MCP Inspector
fastmcp dev mcp_server.py -t streamable-http --port 9000

VS Code Development

1. Open in VS Code:

   code .
   

2. Use Debug Configurations:

   • Debug MCP Server (STDIO): Run with STDIO transport
   • Debug MCP Server (HTTP): Run with HTTP transport
   • Debug Tests: Run the test suite

Configuration

Environment Variables

Create a .env file based on .env.example:

# Server Settings
MCP_HOST=0.0.0.0
MCP_PORT=9000
MCP_DEBUG=false
MCP_SERVER_NAME=MHLABS MCP Server

# Authentication Settings
MCP_ENABLE_AUTH=true
AZURE_TENANT_ID=your-tenant-id-here
AZURE_CLIENT_ID=your-client-id-here
AZURE_JWKS_URI=https://login.microsoftonline.com/your-tenant-id/discovery/v2.0/keys
AZURE_ISSUER=https://sts.windows.net/your-tenant-id/
AZURE_AUDIENCE=api://your-client-id

Authentication

When MCP_ENABLE_AUTH=true, the server expects Azure AD Bearer tokens. Configure your Azure App Registration with the appropriate settings.

For development, set MCP_ENABLE_AUTH=false to disable authentication.

Adding New Services

1. Create Service Class:

   from core.factory import MCPToolBase, Domain
   
   class MyService(MCPToolBase):
       def __init__(self):
           super().__init__(Domain.MY_DOMAIN)
   
       def register_tools(self, mcp):
           @mcp.tool(tags={self.domain.value})
           async def my_tool(param: str) -> str:
               # Tool implementation
               pass
   
       @property
       def tool_count(self) -> int:
           return 1  # Number of tools
   

2. Register in Server:

   # In mcp_server.py (gets registered automatically from services/ directory)
   factory.register_service(MyService())
   

3. Add Domain (if new):

   # In core/factory.py
   class Domain(Enum):
       # ... existing domains
       MY_DOMAIN = "my_domain"
   

MCP Client Usage

Python Client

import asyncio
from fastmcp import Client

client = Client("http://localhost:9000/mcp")

async def main():
    async with client:
        tools = await client.list_tools()
        # tools -> list[mcp.types.Tool]
        # print(tools)
        for tool in tools:
            print(f"Tool: {tool.name}")
        
        result = await client.call_tool("textprep.expand_contraction", {"input_text": "The must've SSN is 859-98-0987. The employee's phone number is 555-555-5555."})
        print("Result:", result)

asyncio.run(main())

Command Line Testing

# Test the server is running
curl http://localhost:9000/mcp/

# With FastMCP CLI for testing
fastmcp dev mcp_server.py -t streamable-http --port 9000

Quick Test

Test STDIO Transport:

# Start server in STDIO mode
python mcp_server.py --debug --no-auth

# Test with client_example.py
python client_example.py

Test HTTP Transport:

# Start HTTP server
python mcp_server.py --transport http --port 9000 --debug --no-auth

# Test with FastMCP client
python -c "
from fastmcp import Client
import asyncio
async def test():
    async with Client('http://localhost:9000/mcp') as client:
        result = await client.call_tool("textprep.expand_contraction", {"input_text": "The must've SSN is 859-98-0987. The employee's phone number is 555-555-5555."})
        print(result)
asyncio.run(test())
"

Test with FastMCP CLI:

# Start with FastMCP CLI
fastmcp run mcp_server.py -t streamable-http --port 9000 -l DEBUG

# Server will be available at: http://127.0.0.1:9000/mcp/

Troubleshooting

Common Issues

1. Import Errors: Make sure you're in the correct directory and dependencies are installed
2. Authentication Errors: Check your Azure AD configuration and tokens
3. Port Conflicts: Change the port in configuration if 9000 is already in use
4. Missing fastmcp: Install with pip install fastmcp

Debug Mode

Enable debug mode for detailed logging:

python mcp_server.py --debug --no-auth

Or set in environment:

MCP_DEBUG=true

Server Arguments

usage: mcp_server.py [-h] [--transport {stdio,http,streamable-http,sse}]
                     [--host HOST] [--port PORT] [--debug] [--no-auth]

MHLABS MCP Server

options:
  -h, --help            show this help message and exit
  --transport, -t       Transport protocol (default: stdio)
  --host HOST           Host to bind to for HTTP transport (default: 127.0.0.1)
  --port, -p PORT       Port to bind to for HTTP transport (default: 9000)
  --debug               Enable debug mode
  --no-auth             Disable authentication

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📄 License

MIT License © 2025 MusaddiqueHussain Labs

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🤝 Contributing

1. Follow the existing code structure and patterns
2. Add tests for new functionality
3. Update documentation for new features
4. Use the provided VS Code configurations for development

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🧠 Learn More

• MCP Protocol: https://modelcontextprotocol.io
• FastMCP GitHub: https://github.com/fastmcp/fastmcp
• LangGraph Integration Guide (coming soon)

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💡 Tip

If you want to embed mhlabs-mcp-tools into a larger MCP-based orchestrator:

from fastmcp import StdioServerParameters
server_params = StdioServerParameters(
    command="python",
    args=["-m", "mhlabs_mcp_tools.server"],
    //env={"MHLABS_MCP_CATEGORY": "textprep,nlp"}
)

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Developed with ❤️ by MusaddiqueHussain Labs