mhlabs-mcp-tools

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.

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

2. Text Preprocessing

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

Quick Start

Development Setup

1. Clone and Navigate:

   bash

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   cd src/mhlabs_mcp_tools
   

2. Install Dependencies:

   Terminal

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   pip install -r requirements.txt
   

3. Configure Environment:

   bash

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

4. Start the Server:

   bash

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   # 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:

   bash

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   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:

   server.ts

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   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:

   python

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

3. Add Domain (if new):

   python

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

MCP Client Usage