Sde MCP
The SD Elements MCP server is a model context protocol service that provides SD Elements API integration, enabling LLMs to interact with the SD Elements secure development lifecycle platform.
2.5 points
7.9K

What is the SD Elements MCP Server?

The SD Elements MCP server is a Model Context Protocol (MCP) server that provides API integration for the SD Elements secure development lifecycle platform. This server allows large language models (LLMs) to interact with SD Elements, enabling the automation and intelligence of the secure development process.

How to Use the SD Elements MCP Server?

By installing and configuring the SD Elements MCP server, users can utilize the command line or integrate it into other tools such as Claude Desktop, Cline, Continue, and Cursor. The server requires setting the SD Elements instance URL and API key as environment variables for proper connection and authentication.

Use Cases

It is suitable for development teams to conduct security testing, risk assessment, task management, and project tracking in the software development lifecycle. It is particularly suitable for scenarios that require combining AI capabilities with the secure development process.

Main Features

Comprehensive API Coverage
Supports all major API endpoints of SD Elements, including project, application, countermeasure, task, investigation, phase, and milestone management.
Secure Authentication
Performs secure authentication through API keys to ensure the security of data access.
Error Handling
Provides comprehensive error handling and validation mechanisms to ensure the reliability and stability of operations.
Flexible Configuration
Supports configuration through environment variables, facilitating adaptation to different deployment requirements.
Modern Python Technology
Built on modern Python packaging tools (such as uv and pyproject.toml) to ensure the maintainability and extensibility of the code.
MCP Compatibility
Fully complies with the Model Context Protocol standard and can be seamlessly integrated into various AI tools.
Advantages
Provides an efficient integration method for development teams with the SD Elements platform.
Supports multiple tools and platforms to enhance the user experience.
Provides comprehensive function coverage to meet diverse secure development needs.
Easy to configure and use, reducing the threshold for use.
Limitations
Depends on the SD Elements platform and cannot run independently.
Requires a certain technical background for configuration and use.
Currently only supports specific tools and platforms, with limited extensibility.

How to Use

Install the Server
Install the SD Elements MCP server from GitHub or PyPI using uvx or pip.
Configure Environment Variables
Set the SD Elements instance URL and API key as environment variables.
Start the Server
After running the server, you can interact with the SD Elements platform through integrated tools.

Usage Examples

Security Testing Automation
Through the SD Elements MCP server, LLMs can automatically execute security testing tasks, improving development efficiency.
Task Management
Development teams can manage tasks in projects through the SD Elements MCP server to ensure that each task is completed on time.
Countermeasure Update
When a new security threat is discovered, the SD Elements MCP server can help quickly update countermeasures.

Frequently Asked Questions

How to obtain the SD Elements API key?
Can the SD Elements MCP server be run locally?
Which tools does the SD Elements MCP server support?
What should I do if I encounter an error?

Related Resources

SD Elements Official Documentation
Learn more details and functions of the SD Elements platform.
GitHub Repository
View the source code and latest updates of the SD Elements MCP server.
Model Context Protocol Specification
Learn about the standards and implementation methods of the Model Context Protocol.

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "sde-elements": {
      "command": "uvx",
      "args": ["git+https://github.com/geoffwhittington/sde-mcp.git"],
      "env": {
        "SDE_HOST": "https://your-sdelements-instance.com",
        "SDE_API_KEY": "your-api-key-here"
      }
    }
  }
}

{
  "mcpServers": {
    "sde-elements": {
      "command": "uvx",
      "args": ["sde-mcp-server"],
      "env": {
        "SDE_HOST": "https://your-sdelements-instance.com",
        "SDE_API_KEY": "your-api-key-here"
      }
    }
  }
}

{
  "mcpServers": {
    "sde-elements": {
      "command": "sde-mcp-server",
      "env": {
        "SDE_HOST": "https://your-sdelements-instance.com",
        "SDE_API_KEY": "your-api-key-here"
      }
    }
  }
}

{
  "mcpServers": {
    "sde-elements": {
      "command": "python",
      "args": ["-m", "sde_mcp_server"],
      "env": {
        "SDE_HOST": "https://your-sdelements-instance.com",
        "SDE_API_KEY": "your-api-key-here"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

V
Vestige
Vestige is an AI memory engine based on cognitive science. By implementing 29 neuroscience modules such as prediction error gating, FSRS - 6 spaced repetition, and memory dreaming, it provides long - term memory capabilities for AI. It includes a 3D visualization dashboard and 21 MCP tools, runs completely locally, and does not require the cloud.
Rust
10.5K
4.5 points
M
Moltbrain
MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.
TypeScript
10.1K
4.5 points
B
Bm.md
A feature-rich Markdown typesetting tool that supports multiple style themes and platform adaptation, providing real-time editing preview, image export, and API integration capabilities
TypeScript
14.8K
5 points
S
Security Detections MCP
Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.
TypeScript
6.7K
4 points
P
Paperbanana
Python
8.9K
5 points
B
Better Icons
An MCP server and CLI tool that provides search and retrieval of over 200,000 icons, supports more than 150 icon libraries, and helps AI assistants and developers quickly obtain and use icons.
TypeScript
8.7K
4.5 points
A
Assistant Ui
assistant - ui is an open - source TypeScript/React library for quickly building production - grade AI chat interfaces, providing composable UI components, streaming responses, accessibility, etc., and supporting multiple AI backends and models.
TypeScript
9.0K
5 points
A
Apify MCP Server
The Apify MCP Server is a tool based on the Model Context Protocol (MCP) that allows AI assistants to extract data from websites such as social media, search engines, and e-commerce through thousands of ready-to-use crawlers, scrapers, and automation tools (Apify Actors). It supports OAuth and Skyfire proxy payment and can be integrated into MCP clients such as Claude and VS Code through HTTPS endpoints or local stdio.
TypeScript
8.7K
5 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
39.1K
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
24.8K
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
80.2K
4.3 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
28.4K
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#
38.4K
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
69.5K
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
24.9K
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
107.1K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase