AI-powered chat system with multiple MCP servers.
LocalAbout AI-powered chat system with multiple MCP servers.
This Python chat client connects Claude to filesystem, Slack, and Brave-Search MCP servers. It selects among local file search, Slack conversations, and web search based on the question.
Key features
- 01Connect filesystem, Slack, and Brave-Search servers
- 02Search specified local folders
- 03Access Slack conversations and channels
- 04Search the web with Brave-Search
- 05Select a server based on the query
Use cases
- 01Find information in local documents
- 02Look up context in Slack conversations
- 03Search the web for current information
MCP support
The chat client connects to multiple MCP servers: filesystem, Slack, and Brave-Search. It chooses which server to use based on the query.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEAI-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.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.