AI-powered chat system with multiple MCP servers.
AI-powered Chat System with multiple MCP servers.
What is the MCP Chat System?
The MCP Chat System is an AI-powered chat application that connects to multiple Model Context Protocol (MCP) servers, enabling seamless interaction with various AI functionalities.
How to use the MCP Chat System?
To use the MCP Chat System, clone the repository, set up your environment with the necessary API keys, and run the client with the desired server arguments.
Key features of the MCP Chat System?
- Integration with multiple MCP servers for enhanced AI capabilities.
- Access to local files, Slack conversations, and real-time web search.
- Intelligent server selection based on user queries.
Use cases of the MCP Chat System?
- Accessing and retrieving information from local documents.
- Engaging in conversations using Slack integration.
- Performing real-time web searches to provide up-to-date information.
FAQ from the MCP Chat System?
- Can I use the MCP Chat System for different types of queries?
Yes! The system intelligently determines the best server to use based on your query type.
- Is there a cost associated with using the MCP Chat System?
The MCP Chat System is open-source and free to use under the MIT License.
AI-powered chat system with multiple MCP servers.
Overview 🌟
MCP is a powerful client-server architecture that enables host applications to connect with multiple AI servers seamlessly. This system offers enhanced capabilities through specialized MCP servers:
-
MCP Filesystem: Allows Claude to search and retrieve information from your specified local folders, making your documents and files accessible to the AI.
-
MCP Slack Server: Connects to your Slack workspace, enabling Claude to access and reference your conversations, channels, and shared resources.
-
MCP Brave-Search: Provides real-time web search capabilities, allowing Claude to find and incorporate the latest information from the internet.
The system intelligently determines which server to utilize based on your queries. Claude automatically analyzes your questions and decides whether to search your local files, check Slack history, or perform a web search - all without requiring explicit instructions from you.
General Architecture 🛠️
At its core, MCP follows a client-server architecture where a host application can connect to multiple servers:
Getting Started! 🚀
Prerequisites 🤝
You need to install uv to run this project.
# MacOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Setup ⚙️
- Clone the repository.
git clone https://github.com/kira1228/mcp-chat-bot.git
cd mcp-chat-bot
- Create a
.envfile with your API keys:
# Create the .env file
touch .env
# Add your API credentials
# ANTHROPIC_API_KEY: Used for Claude AI integration
echo "ANTHROPIC_API_KEY=<your api key>" >> .env
# SLACK_BOT_TOKEN & SLACK_TEAM_ID: Required for Slack integration
echo "SLACK_BOT_TOKEN=<your api key>" >> .env
echo "SLACK_TEAM_ID=<your api key>" >> .env
# BRAVE_API_KEY: Used for Brave search capabilities
echo "BRAVE_API_KEY=<your api key>" >> .env
- Create a virtual environment and install the dependencies.
# MacOS/Linux
uv venv
source .venv/bin/activate
uv sync
# Windows
uv venv
.venv\Scripts\activate
uv sync
Usage 💻
Run the client with arguments for the server.
uv run client.py path/to/dir/you/want/to/use
References 📚
License 🔑
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.