MCP Tool Kit
STDIOA modular server implementation for building high precision vertical AI agents.
A modular server implementation for building high precision vertical AI agents.
A modular server implementation for building high precision vertical AI agents. Intended for use building high precision vertical AI agents, but can deploy to gain access to general tool functionality.
Uses >=50% less code than the Python MCP SDK alone.
Here's a concrete example of Claude invoking a vertical agent:
User: "I need a comprehensive analysis of the electric vehicle market for a presentation tomorrow."
Claude: [recognizes this requires multiple tools and domain expertise]
Claude: "I'll help you with that comprehensive EV market analysis. I'll need to gather the latest market data, news, and trends. This will take a moment..."
[Behind the scenes, Claude calls a MarketAnalysisAgent]
Claude -> MarketAnalysisAgent.analyze_market(
sector="electric vehicles",
include_news=True,
include_market_data=True,
create_presentation=True
)
[The agent orchestrates multiple tool calls using your toolkit]
- news_search for recent EV news
- brave_web_search for market data
- sequential_thinking for analysis
- write_file to save the report
- ppt_create_presentation to generate slides
[Agent returns results to Claude]
Claude: "I've analyzed the electric vehicle market for you. Here are the key findings:
1. Tesla continues to lead with 65% market share in North America
2. BYD has overtaken VW in global sales volume
3. Battery technology breakthroughs are accelerating adoption
I've also created a presentation with detailed charts and data. You can find it saved as 'EV_Market_Analysis.pptx' in your working directory."
The MCP Unified Server provides a unified interface for Claude to interact with various external systems and tools including:
Note: ensure that you have git downloaded (https://git-scm.com/downloads) and Docker downloaded (https://www.docker.com/products/docker-desktop/) and running. You also must ensure the git executable file is added to path (instructions towards end of this README).
clone https://github.com/getfounded/mcp-tool-kit.git cd mcp-tool-kit
docker-compose up
Option 2 - Direct Docker command:
docker run -p 8000:8000 -v ~/documents:/app/documents getfounded/mcp-tool-kit:latest
The repository includes a sample Claude desktop configuration file (claude_desktop_config.json
) that you can use:
{ "mcpServers": { "unified": { "command": "docker", "args": [ "exec", "-i", "mcp-tool-kit-mcp-server", "python", "-u", "mcp_unified_server.py" ], "useStdio": true } } }
If you are getting errors running docker, it is likely that the image name is incorrect in the Claude desktop configuration file. A common fix is to use the following json for configuration:
{ "mcpServers": { "unified": { "command": "docker", "args": [ "exec", "-i", "mcp-tool-kit-mcp-server-1", "python", "-u", "mcp_unified_server.py" ], "useStdio": true } } }
# Simple installation pip install mcptoolkit # Launch the server with default configuration mcptoolkit-server
Local server basic configuration:
{ "tools": [ { "name": "MCP Toolkit", "url": "http://localhost:8000" } ], "settings": { "allowed_directories": ["~/Documents", "~/Downloads"], "default_tools": ["MCP Toolkit"] } }
You can import this configuration in the Claude desktop app or use it as a reference to create your own.
You now have immediate access to powerful capabilities including file operations, web search, time tools, and more—without requiring any API keys or complex setup.
After cloning the repository, you have two options to configure your environment variables:
Run the setup script which will guide you through setting up your environment variables:
python setup_env.py
This script will create a .env
file in the repository with your configuration.
Alternatively, you can manually create a .env
file in the repository root with the following variables:
# API Keys for external services
BRAVE_API_KEY=your_brave_api_key
NEWS_API_KEY=your_news_api_key
FRED_API_KEY=your_fred_api_key
# Application configuration
STREAMLIT_APPS_DIR=/path/to/streamlit/apps
MCP_FILESYSTEM_DIRS=/path/to/allowed/dir1,/path/to/allowed/dir2
MCP_LOG_LEVEL=info
Once set up, you can ask Claude to use the tools with prompts like:
read_file
: Read contents of a file
read_multiple_files
: Read multiple files simultaneously
write_file
: Create or overwrite a file
edit_file
: Make line-based edits to a file
create_directory
: Create a new directory
list_directory
: Get directory contents
directory_tree
: Get a recursive tree view
move_file
: Move or rename files/directories
search_files
: Search for files matching a pattern
get_file_info
: Get file metadata
list_allowed_directories
: List allowed directories
Browser_Automation:
playwright_launch_browser
: Launch a new browser instanceplaywright_navigate
: Navigate to a URLplaywright_screenshot
: Take a screenshotplaywright_click
: Click on an elementplaywright_fill
: Fill an input fieldplaywright_evaluate
: Execute JavaScriptplaywright_get_content
: Get the HTML content of a pagerun_agent
: Execute a registered agent with parameterslist_agents
: List all available agents and their metadataYahoo Finance:
yfinance
: Get stock quotes and historical datayfinance_get_quote
: Get current stock quoteyfinance_get_history
: Get historical stock datayfinance_get_info
: Get detailed company informationyfinance_get_options
: Get options chain datayfinance_get_recommendations
: Get analyst recommendationsFRED (Federal Reserve Economic Data):
fred_get_series
: Get economic data seriesfred_get_series_info
: Get metadata about a seriesfred_search
: Search for economic data seriesfred_get_category
: Browse data by categoryfred_get_releases
: Get economic data releasesfred_get_sources
: Get data sourcesget_current_time
: Get current time in a specified timezoneconvert_time
: Convert time between timezonessequentialthinking
: A tool for breaking down complex problems using a step-by-step thinking processbrave_web_search
: Perform web searchesbrave_local_search
: Search for local businesses and placesworldbank_get_indicator
: Get indicator data for a countrynews_top_headlines
: Get top news headlinesnews_search
: Search for news articlesnews_sources
: List available news sourcesppt_create_presentation
: Create a new PowerPoint presentationppt_open_presentation
: Open an existing presentationppt_save_presentation
: Save a presentationppt_add_slide
: Add a new slideppt_add_text
: Add text to a slideppt_add_image
: Add an image to a slideppt_add_chart
: Add a chart to a slideppt_add_table
: Add a table to a slideppt_analyze_presentation
: Analyze presentation structureppt_enhance_presentation
: Suggest enhancementsppt_generate_presentation
: Generate a presentation from textppt_command
: Process natural language commandsFor a complete list of available tools, see the documentation or browse the tools directory. For a complete list of available tools, see the documentation or browse the tools directory.
tools
directory (e.g., my_tool.py
)mcp_unified_server.py
to import and register your new moduleYou can use Docker for development to ensure a consistent environment:
# Build a development image docker build -t mcp-tool-kit:dev . # Run with source code mounted for development docker run -p 8000:8000 \ -v $(pwd):/app \ -v ~/documents:/app/documents \ mcp-tool-kit:dev
This mounts your local repository into the container, so changes to the code are reflected immediately (for most files).
The MCP Tool Kit represents a paradigm shift in how we conceptualize the relationship between human intelligence and AI systems. Rather than positioning AI as a mere tool for task automation, this framework establishes a cognitive partnership where human strategic thinking and AI operational capabilities complement each other in profound ways.
The agentic architecture embodies a transformative vision: AI systems that can independently interpret context, make decisions within bounded parameters, and execute complex sequences of actions—all while maintaining human oversight and strategic direction. This represents not merely a technological advance, but a fundamentally new model for human-machine collaboration.
In this evolving cognitive landscape, the most successful implementations will be those that thoughtfully balance technological potential with human capabilities, creating interfaces that enhance rather than replace human decision-making and creativity.
.env
fileMCP_FILESYSTEM_DIRS
#To add Git to the PATH on Windows, follow these steps:
Locate Git Installation: Determine the path where Git is installed on your system. Common paths include C:\Program Files\Git\bin\git.exe and C:\Program Files\Git\cmd for a standard Git installation, or C:\Users<username>\AppData\Local\GitHub\PortableGit_
Edit Environment Variables: Open the "Edit Environment Variables" app either through the Control Panel or by searching for "Edit the system environment variables" in the Start menu. Under the "System variables" section, find the "Path" variable, click "Edit...", and add the path to the Git executable and command files. Ensure there are no spaces around the semicolons separating paths.
Save Changes: After adding the Git paths, click "OK" to save your changes. Close and reopen any command prompt windows to apply the new PATH settings.
Verify Installation: Open a command prompt and run git --version to verify that Git is accessible from the command line.
The MCP Unified Server is licensed under the MIT License.
This project uses several open-source libraries and APIs: