Confidential guide on numerology and astrology, based of GG33 Public information

local_mcp_server-client_EAG-S-4
3 years
Works with Finder
1
Github Watches
0
Github Forks
0
Github Stars
🧠 mcp_server-client_EAG-S-4 - Local Setup
This repository provides a minimal implementation to set up and interact with the MCP (Modular Computation Protocol) locally. It consists of a server that exposes various computational tools and a client that communicates with the server to invoke those tools.
The project is managed using uv
, a fast Python package manager and workflow tool.
📂 Project Structure
-
mcp_server.py
— Hosts the MCP server with 28 tools available for interaction. -
mcp_client.py
— The entry point of the project; runs a client that connects to the MCP server and calls its tools. -
pyproject.toml
— Project configuration and dependencies using PEP 621. -
uv.lock
— Auto-generated lockfile for reproducible installations usinguv
. -
token.env
— Environment file that likely contains secrets or tokens. -
README.md
— Project documentation."""
🛠️ Available Tools on the MCP Server
🔢 Math Tools
-
add(a, b)
— Add two numbers -
add_list(l)
— Add all numbers in a list -
subtract(a, b)
— Subtract two numbers -
multiply(a, b)
— Multiply two numbers -
divide(a, b)
— Divide two numbers -
power(a, b)
— Raise a to the power of b -
sqrt(a)
— Square root -
cbrt(a)
— Cube root -
factorial(a)
— Factorial -
log(a)
— Natural logarithm -
remainder(a, b)
— Modulus operation -
sin(a)
— Sine -
cos(a)
— Cosine -
tan(a)
— Tangent -
mine(a, b)
— Special mining tool -
int_list_to_exponential_sum(int_list)
— Sum of exponentials of integers -
fibonacci_numbers(n)
— First n Fibonacci numbers
🧠 String/Image Tools
-
strings_to_chars_to_int(string)
— Convert characters to ASCII -
create_thumbnail(image_path)
— Generate a thumbnail from an image
🖌️ Pinta Automation Tools
-
open_pinta_application()
— Launch and focus Pinta -
select_rectangle_tool()
-
select_text_tool()
-
select_circle_tool()
-
draw_rectangle(x1, y1, x2, y2)
-
write_text_inside_rectangle(text, x1, y1, x2, y2)
-
draw_circle(x1, y1, radius)
-
get_lines_of_rectangle(x1, y1, x2, y2)
— Return lines from rectangle coordinates -
get_midpoint_of_line(x1, y1, x2, y2)
— Return midpoint of a line
🚀 Getting Started
1. Clone the Repository
git clone https://github.com/your-username/mcp-protocol.git
cd mcp-protocol
2. Install uv
(if not already installed)
curl -Ls https://astral.sh/uv/install.sh | sh
Verify installation:
uv --version
3. Set Up the Project Environment
uv venv
source .venv/bin/activate # or .venv\Scripts\activate on Windows
uv pip install -r pyproject.toml
If
requirements.txt
doesn't exist:uv pip freeze > requirements.txt
4. Test MCP Server with GUI client
mcp dev mcp_server.py
5. Run the Client
python mcp_client.py
📌 Notes
- Ensure Pinta is installed if you're using Pinta-related tools.
- Image tools like
create_thumbnail
require valid image paths. -
mcp_client.py
is the main entry point to interact with the protocol.
📄 License
MIT License. Feel free to fork, modify, and contribute.
🤝 Contributing
Pull requests are welcome. For major changes, please open an issue first.
相关推荐
Converts Figma frames into front-end code for various mobile frameworks.
Advanced software engineer GPT that excels through nailing the basics.
Take an adjectivised noun, and create images making it progressively more adjective!
Siri Shortcut Finder – your go-to place for discovering amazing Siri Shortcuts with ease
I find academic articles and books for research and literature reviews.
Discover the most comprehensive and up-to-date collection of MCP servers in the market. This repository serves as a centralized hub, offering an extensive catalog of open-source and proprietary MCP servers, complete with features, documentation links, and contributors.
Micropython I2C-based manipulation of the MCP series GPIO expander, derived from Adafruit_MCP230xx
Bridge between Ollama and MCP servers, enabling local LLMs to use Model Context Protocol tools
🧑🚀 全世界最好的LLM资料总结(Agent框架、辅助编程、数据处理、模型训练、模型推理、o1 模型、MCP、小语言模型、视觉语言模型) | Summary of the world's best LLM resources.
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more.
Reviews

user_1mjauHJq
I've been using local_mcp_server-client_EAG-S-4 by devdastl, and it has significantly improved my workflow. The server-client model is efficient and the GitHub resources are well-documented. It's a must-try for anyone looking to streamline their processes. Highly recommend!