MCP Server for Local
by Dreamboat-Rachel
A local proxy server and client implementation based on MCP (Multi-Component Platform), providing various AI tool calling capabilities. It integrates weather queries, Google search, camera control, image generation, and intelligent dialogue.
Last updated: N/A
What is MCP Server for Local?
MCP Server for Local is a local proxy server and client built on the Multi-Component Platform (MCP). It allows users to access and utilize various AI tools like weather queries, Google search, camera control, image generation using ComfyUI, and intelligent dialogue powered by DashScope.
How to use MCP Server for Local?
First, clone the repository and set up a virtual environment. Install the required dependencies using uv pip install -r requirements.txt. Configure the environment variables in the .env file, including API keys and file paths. Then, navigate to the src/mcp directory and run the client using uv run .\client\mcp_client.py .\proxy\proxy_server.py. You can then interact with the server by entering commands in the client.
Key features of MCP Server for Local
Real-time weather queries
Intelligent Google search
Camera control with facial expression analysis
AI image generation with ComfyUI
Intelligent dialogue based on DashScope
Use cases of MCP Server for Local
Quickly access weather information for any location.
Perform intelligent web searches directly from the command line.
Control a camera to take photos or analyze facial expressions.
Generate images from text prompts using AI.
Engage in intelligent conversations with an AI assistant.
FAQ from MCP Server for Local
What should I do if dependency installation fails?
What should I do if dependency installation fails?
Try clearing the cache and reinstalling the dependencies using uv pip cache purge followed by uv pip install -r requirements.txt.
What if I encounter issues with the virtual environment?
What if I encounter issues with the virtual environment?
Try recreating the virtual environment by deleting the .venv directory and running python -m venv .venv again.
How do I resolve permission issues on Linux?
How do I resolve permission issues on Linux?
Use the command chmod +x src/mcp/proxy/proxy_server.py and chmod +x src/mcp/client/mcp_client.py to grant execute permissions to the server and client scripts.
What if I have problems with Chrome or ChromeDriver?
What if I have problems with Chrome or ChromeDriver?
Ensure that your Chrome and ChromeDriver versions match. Verify that the Chrome path is correct in the .env file and that you have sufficient permissions to run Chrome. If driver issues persist, manually download the corresponding ChromeDriver version.
What if I encounter API key issues?
What if I encounter API key issues?
Double-check the API keys in your .env file for accuracy. Ensure that the API keys have sufficient quota and that your network connection is stable.