MCP Civil Tools
M

MCP Civil Tools

This project is a Python server based on the MCP protocol, providing functions for querying and calculating soil and water conservation technical specifications, including engineering calculations such as Manning's coefficient, earth pressure coefficient, drainage ditch flow velocity, and slope stability, as well as the conversion between latitude and longitude and UTM/TWD97 coordinates in Taiwan region. It is suitable for AI application integration.
2.5 points
8.4K

What is MCP Civil Tools?

This is a professional civil engineering calculation server that transforms the Taiwan Soil and Water Conservation Technical Specifications (2023 Edition) into an intelligent tool that can be queried through natural language. It supports more than 20 professional calculation functions such as Manning's coefficient query, earth pressure calculation, drainage ditch design, and slope stability analysis.

How to use it?

Ask questions directly in natural language through a client that supports the MCP protocol (such as Claude Desktop), or call the calculation functions through the HTTP API. Professional calculation results can be obtained without programming.

Applicable scenarios

In the field of civil engineering such as soil and water conservation design, drainage system planning, retaining wall inspection, and slope stability evaluation, it is especially suitable for scenarios that require quick query of specification parameters or verification of design schemes.

Main functions

Coordinate conversion
Bidirectional conversion between latitude and longitude and UTM/TWD97 coordinates in Taiwan region, supporting custom projection parameters
Hydraulic calculation
Calculate the flow velocity and flow depth of drainage sections, supporting 7 types of cross - sections such as rectangular, trapezoidal, and circular, and automatically checking the water depth and flow velocity specifications
Slope stability analysis
Calculate the safety factor and evaluate the stability, considering factors such as slope, soil parameters, and groundwater level
Retaining wall inspection
Check the sliding/tilting safety factors of gravity retaining walls, supporting normal and seismic conditions
Soil erosion calculation
Calculate the soil loss using the USLE formula, with a built - in database of rainfall erosion index R values for the whole of Taiwan
Advantages
Natural language interaction, no need to memorize complex instructions
Instantly return the specification compliance check results
The calculation process is transparent, providing complete formulas and basis articles
Support batch calculation and report generation
Limitations
The calculation results need to be reviewed by professionals
Currently only applicable to Taiwan region specifications
Some complex working conditions require manual input of parameters

How to use

Installation preparation
Ensure that Python 3.8+ is installed. It is recommended to use a virtual environment.
Install dependencies
Install the necessary Python packages.
Start the service
Select the startup mode: - CLI mode for direct interaction - HTTP service for API calls

Usage examples

Drainage ditch design verification
Verify whether the concrete drainage ditch design meets the specification requirements
Retaining wall stability analysis
Evaluate the safety of the retaining wall under earthquake conditions

Frequently Asked Questions

How to query the available material list?
What should I do if there is a difference between the calculation result and the manual calculation?
Does it support custom material parameters?

Related resources

Soil and Water Conservation Technical Specifications
The latest version of Taiwan Soil and Water Conservation Technical Specifications
GitHub Repository
Project source code and issue tracking
MCP Protocol Description
Official documentation of the Model Context Protocol

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "MCP-civil-tools": {
      "command": "path/.venv/Scripts/python.exe",
      "args": [
        "path/src/mcp_server.py"
      ]
    }
  }
}
或是
    "MCP-civil-tools": {
      "command": "C:/TOMO/MCP-civil-tools/.venv/Scripts/python.exe",
      "args": [
        "C:/TOMO/MCP-civil-tools/src/mcp_server.py"
      ],
      "disabled": true,
      "autoApprove": []
    },
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

R
Runno
Runno is a collection of JavaScript toolkits for securely running code in multiple programming languages in environments such as browsers and Node.js. It achieves sandboxed execution through WebAssembly and WASI, supports languages such as Python, Ruby, JavaScript, SQLite, C/C++, and provides integration methods such as web components and MCP servers.
TypeScript
6.6K
5 points
S
Shadcn Ui MCP Server
An MCP server that provides shadcn/ui component integration for AI workflows, supporting React, Svelte, and Vue frameworks. It includes functions for accessing component source code, examples, and metadata.
TypeScript
13.7K
5 points
A
Annas MCP
The MCP server and CLI tool of Anna's Archive are used to search for and download documents on the platform and support access through an API key.
Go
10.9K
4.5 points
M
MCP Server Weread
The WeRead MCP Server is a lightweight service that bridges WeRead data and AI clients, enabling in - depth interaction between reading notes and AI.
TypeScript
12.8K
4 points
M
MCP Youtube
Download YouTube subtitles via yt - dlp and connect to Claude.ai through the MCP protocol for video content analysis
TypeScript
11.5K
4 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
30.3K
5 points
S
Supermemory
Supermemory is an AI-driven memory engine designed to provide contextual knowledge for LLMs by integrating personal data, enabling intelligent management and retrieval of information.
TypeScript
23.6K
5 points
S
Sequential Thinking MCP Server
A structured thinking server based on the MCP protocol that helps break down complex problems and generate summaries by defining thinking stages
Python
26.9K
4.5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
21.9K
4.3 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
30.3K
5 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
18.0K
4.5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
63.4K
4.3 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
28.0K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
57.9K
4.5 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
19.9K
4.5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
85.6K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase