Mhlabs Mcp Tools

io.github.MusaddiqueHussainLabsPublished by GitHub account MusaddiqueHussainLabsv3.0.0Updated Nov 3, 2026

An MCP server that provides text preprocessing, NLP components, and document analysis

VerifiedSTDIODesktop onlyData & AnalyticsAI & ML

Overview

AI-generated overview

A local Python MCP server exposing text preprocessing, NLP components and document analysis tools for cleaning and analyzing text.

What you can do
  • Clean text: lowercase/uppercase, strip numbers, URLs, punctuation, special characters, whitespace, HTML, emojis and emoticons
  • Redact or remove sensitive patterns such as emails, phone numbers, SSNs and credit card numbers
  • Normalize text: Unicode normalization, contraction expansion, chat-word and emoji/emoticon conversion, stopword, frequent-word and rare-word removal
  • Tokenize words and sentences, stem and lemmatize
  • Run NLP components: part-of-speech tagging, morphology, dependency parsing, named entity recognition and normalization
  • Chain several steps through a combined preprocessing function
When to use it
Useful when an assistant needs to clean, anonymize or normalize raw text before analysis, or to run basic NLP tasks such as tokenization, POS tagging, lemmatization and entity recognition locally without sending text to an external service.
Requirements
Runs as a local Python process installed from the PyPI package mhlabs-mcp-tools, with dependencies installed via pip (including fastmcp). Default STDIO transport; HTTP/SSE modes bind a port. Optional Azure AD authentication uses environment variables such as MCP_ENABLE_AUTH, AZURE_TENANT_ID, AZURE_CLIENT_ID, AZURE_JWKS_URI, AZURE_ISSUER and AZURE_AUDIENCE.
Before you install
Text passed to the tools is processed by the local server; if you switch to HTTP transport and bind a non-local host, the endpoint may be reachable by others. Authentication is optional and can be turned off with MCP_ENABLE_AUTH=false or the no-auth flag, so keep it enabled for shared deployments. Azure AD settings are supplied through environment variables and should be kept out of version control.

Installation

In SourceWeft

  1. Open Mhlabs Mcp Tools in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

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

Component TypeDescription
tokenizeText tokenization
posPart-of-Speech tagging
lemmaWord lemmatization
morphologyStudy of word forms
depDependency parsing
nerNamed Entity Recognition
normText normalization

2. Text Preprocessing

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

FunctionDescription
to_lowerConvert text to lowercase
to_upperConvert text to uppercase
remove_numberRemove numerical characters
remove_itemized_bullet_and_numberingEliminate itemized/bullet-point numbering
remove_urlRemove URLs from text
remove_punctuationRemove punctuation marks
remove_special_characterRemove special characters
keep_alpha_numericKeep only alphanumeric characters
remove_whitespaceRemove excess whitespace
normalize_unicodeNormalize Unicode characters
remove_stopwordEliminate common stopwords
remove_freqwordsRemove frequently occurring words
remove_rarewordsRemove rare words
remove_emailRemove email addresses
remove_phone_numberRemove phone numbers
remove_ssnRemove Social Security Numbers (SSN)
remove_credit_card_numberRemove credit card numbers
remove_emojiRemove emojis
remove_emoticonsRemove emoticons
convert_emoticons_to_wordsConvert emoticons to words
convert_emojis_to_wordsConvert emojis to words
remove_htmlRemove HTML tags
chat_words_conversionConvert chat language to standard English
expand_contractionExpand contractions (e.g., "can't" to "cannot")
tokenize_wordTokenize words
tokenize_sentenceTokenize sentences
stem_wordStem words
lemmatize_wordLemmatize words
preprocess_textCombine multiple preprocessing steps into one function

Quick Start

Development Setup

  1. Clone and Navigate:

    bash
    cd src/mhlabs_mcp_tools
  2. Install Dependencies:

    bash
    pip install -r requirements.txt
  3. Configure Environment:

    bash
    cp .env.example .env# Edit .env with your configuration
  4. Start the Server:

    bash
    # Default STDIO transport (for local MCP clients)python mcp_server.py
    # HTTP transport (for web-based clients)python mcp_server.py --transport http --port 9000orafter installed mhlabs-mcp-toolspython -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 disabledpython 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

bash
# Standard HTTP serverfastmcp run mcp_server.py -t streamable-http --port 9000 -l DEBUG
# With custom hostfastmcp 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 Inspectorfastmcp dev mcp_server.py -t streamable-http --port 9000

VS Code Development

  1. Open in VS Code:

    bash
    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:

env
# Server SettingsMCP_HOST=0.0.0.0MCP_PORT=9000MCP_DEBUG=falseMCP_SERVER_NAME=MHLABS MCP Server
# Authentication SettingsMCP_ENABLE_AUTH=trueAZURE_TENANT_ID=your-tenant-id-hereAZURE_CLIENT_ID=your-client-id-hereAZURE_JWKS_URI=https://login.microsoftonline.com/your-tenant-id/discovery/v2.0/keysAZURE_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:

    python
    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
    # In mcp_server.py (gets registered automatically from services/ directory)factory.register_service(MyService())
  3. Add Domain (if new):

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

MCP Client Usage

Python Client

python
import asynciofrom 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

bash
# Test the server is runningcurl http://localhost:9000/mcp/
# With FastMCP CLI for testingfastmcp dev mcp_server.py -t streamable-http --port 9000

Quick Test

Test STDIO Transport:

bash
# Start server in STDIO modepython mcp_server.py --debug --no-auth
# Test with client_example.pypython client_example.py

Test HTTP Transport:

bash
# Start HTTP serverpython mcp_server.py --transport http --port 9000 --debug --no-auth
# Test with FastMCP clientpython -c "from fastmcp import Clientimport asyncioasync 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:

bash
# Start with FastMCP CLIfastmcp 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:

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

Or set in environment:

env
MCP_DEBUG=true

Server Arguments

bash
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

📄 License

MIT License © 2025 MusaddiqueHussain Labs


🤝 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

🧠 Learn More


💡 Tip

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

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

Developed with ❤️ by MusaddiqueHussain Labs

Source: README.md at commit 6c1b271

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v3.0.0LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts