
Devici MCP Server
Provides LLM tools to interact with the Devici API, enabling management of threat modeling resources including users, collections, threat models, components, threats, mitigations, and teams.
Tools
get_users
Get users from Devici with pagination
get_user
Get a specific user by ID
search_users
Search users by field and text
invite_user
Invite a new user to Devici
get_collections
Get collections from Devici with pagination
get_collection
Get a specific collection by ID
create_collection
Create a new collection
get_threat_models
Get threat models from Devici with pagination
get_threat_models_by_collection
Get threat models for a specific collection
get_threat_model
Get a specific threat model by ID
create_threat_model
Create a new threat model
get_components
Get components from Devici with pagination
get_component
Get a specific component by ID
get_components_by_canvas
Get components for a specific canvas
get_threat
Get a specific threat by ID
get_threats_by_component
Get threats for a specific component
get_mitigations
Get mitigations from Devici with pagination
get_mitigation
Get a specific mitigation by ID
get_mitigations_by_threat
Get mitigations for a specific threat
get_teams
Get teams from Devici with pagination
get_team
Get a specific team by ID
get_dashboard_types
Get available dashboard chart types
get_dashboard_data
Get dashboard data for a specific chart type
get_threats
Get threats from Devici with pagination
get_threat_models_report
Get threat models report data
README
Devici MCP Server
A Model Context Protocol (MCP) server for interacting with the Devici API. This server provides LLM tools to manage users, collections, threat models, components, threats, mitigations, teams, and dashboard data through the Devici platform.
Features
The Devici MCP Server provides tools for:
User Management
- Get users with pagination
- Get specific user by ID
- Search users by field and text
- Invite new users
Collections Management
- Get collections with pagination
- Get specific collection by ID
- Create new collections
Threat Models Management
- Get all threat models with pagination
- Get threat models by collection
- Get specific threat model by ID
- Create new threat models
Components Management
- Get components with pagination
- Get specific component by ID
- Get components by canvas
- Create new components
Threats Management
- Get threats with pagination
- Get specific threat by ID
- Get threats by component
- Create new threats
Mitigations Management
- Get mitigations with pagination
- Get specific mitigation by ID
- Get mitigations by threat
- Create new mitigations
Teams Management
- Get teams with pagination
- Get specific team by ID
- Get team users
- Create new teams
Dashboard & Reports
- Get dashboard data
- Get report data
- Get threat model statistics
Comments & Audit
- Get comments with pagination
- Get specific comment by ID
- Get audit logs
Codex Integration
- Get codex attributes
- Get codex mitigations
- Get codex threats
Quick Start
Using uvx (recommended)
Option 1: From GitHub (Current)
uvx git+https://github.com/geoffwhittington/devici-mcp.git
Option 2: From PyPI (Future - when published)
uvx devici-mcp-server
Using uv
Install from GitHub
uv pip install git+https://github.com/geoffwhittington/devici-mcp.git
devici-mcp-server
Install from PyPI (when available)
uv pip install devici-mcp-server
devici-mcp-server
Using pip
Install from GitHub
pip install git+https://github.com/geoffwhittington/devici-mcp.git
devici-mcp-server
Install from PyPI (when available)
pip install devici-mcp-server
devici-mcp-server
Configuration
The server requires three environment variables:
DEVICI_API_BASE_URL
: Your Devici instance URL (e.g.,https://api.devici.com/v1
)DEVICI_CLIENT_ID
: Your Devici client IDDEVICI_CLIENT_SECRET
: Your Devici client secret
Setting Environment Variables
Option 1: Environment Variables
export DEVICI_API_BASE_URL="https://api.devici.com/v1"
export DEVICI_CLIENT_ID="your-client-id-here"
export DEVICI_CLIENT_SECRET="your-client-secret-here"
Option 2: .env File
Create a .env
file in your working directory:
DEVICI_API_BASE_URL=https://api.devici.com/v1
DEVICI_CLIENT_ID=your-client-id-here
DEVICI_CLIENT_SECRET=your-client-secret-here
Getting Your API Credentials
- Log into your Devici instance
- Go to Settings > API Access
- Generate a new client ID and secret
- Copy the values for use as
DEVICI_CLIENT_ID
andDEVICI_CLIENT_SECRET
MCP Client Configuration
Claude Desktop
Add this to your Claude Desktop configuration file:
Option 1: From GitHub (Current)
{
"mcpServers": {
"devici": {
"command": "uvx",
"args": ["git+https://github.com/geoffwhittington/devici-mcp.git"],
"env": {
"DEVICI_API_BASE_URL": "https://api.devici.com/v1",
"DEVICI_CLIENT_ID": "your-client-id-here",
"DEVICI_CLIENT_SECRET": "your-client-secret-here"
}
}
}
}
Option 2: From PyPI (Future)
{
"mcpServers": {
"devici": {
"command": "uvx",
"args": ["devici-mcp-server"],
"env": {
"DEVICI_API_BASE_URL": "https://api.devici.com/v1",
"DEVICI_CLIENT_ID": "your-client-id-here",
"DEVICI_CLIENT_SECRET": "your-client-secret-here"
}
}
}
}
Cline
Add this to your Cline MCP settings:
From GitHub (Current)
{
"mcpServers": {
"devici": {
"command": "uvx",
"args": ["git+https://github.com/geoffwhittington/devici-mcp.git"],
"env": {
"DEVICI_API_BASE_URL": "https://api.devici.com/v1",
"DEVICI_CLIENT_ID": "your-client-id-here",
"DEVICI_CLIENT_SECRET": "your-client-secret-here"
}
}
}
}
Continue
Add this to your Continue configuration:
From GitHub (Current)
{
"mcpServers": {
"devici": {
"command": "uvx",
"args": ["git+https://github.com/geoffwhittington/devici-mcp.git"],
"env": {
"DEVICI_API_BASE_URL": "https://api.devici.com/api/v1",
"DEVICI_CLIENT_ID": "your-client-id-here",
"DEVICI_CLIENT_SECRET": "your-client-secret-here"
}
}
}
}
Cursor
Add this to your Cursor configuration file:
Option 1: From GitHub (Current)
{
"mcpServers": {
"devici": {
"command": "uvx",
"args": ["git+https://github.com/geoffwhittington/devici-mcp.git"],
"env": {
"DEVICI_API_BASE_URL": "https://api.devici.com/api/v1",
"DEVICI_CLIENT_ID": "your-client-id-here",
"DEVICI_CLIENT_SECRET": "your-client-secret-here"
}
}
}
}
Option 2: Using local installation
If you have the package installed locally:
{
"mcpServers": {
"devici": {
"command": "devici-mcp-server",
"env": {
"DEVICI_API_BASE_URL": "https://api.devici.com/api/v1",
"DEVICI_CLIENT_ID": "your-client-id-here",
"DEVICI_CLIENT_SECRET": "your-client-secret-here"
}
}
}
}
Option 3: Using Python module directly
{
"mcpServers": {
"devici": {
"command": "python",
"args": ["-m", "devici_mcp_server"],
"env": {
"DEVICI_API_BASE_URL": "https://api.devici.com/api/v1",
"DEVICI_CLIENT_ID": "your-client-id-here",
"DEVICI_CLIENT_SECRET": "your-client-secret-here"
}
}
}
}
Development
Prerequisites
- uv installed
- Python 3.10 or higher
Setup
# Clone the repository
git clone <repository-url>
cd devici-mcp
# Create virtual environment and install dependencies
uv sync
# Run in development mode
uv run python -m devici_mcp_server
Testing
# Run the import test
uv run python test_basic.py
# Test with environment variables
DEVICI_API_BASE_URL=https://api.devici.com/api/v1 DEVICI_CLIENT_ID=test DEVICI_CLIENT_SECRET=test uv run python -m devici_mcp_server
Building
# Build the package
uv build
# Install locally for testing
uv pip install dist/*.whl
Features
- Full API Coverage: Supports all major Devici API endpoints
- Authentication: Secure client ID/secret-based authentication
- Error Handling: Comprehensive error handling and validation
- Environment Configuration: Flexible configuration via environment variables
- Modern Python: Built with modern Python packaging (uv, pyproject.toml)
- MCP Compliant: Fully compatible with the Model Context Protocol
API Coverage
This server provides access to:
- Users and Teams
- Collections and Threat Models
- Components and Threats
- Mitigations and Comments
- Dashboard Data and Reports
- Audit Logs and Codex Integration
- Search and Bulk Operations
License
This project is licensed under the MIT License - see the LICENSE file for details.
Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature
) - Commit your changes (
git commit -m 'Add some amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
Support
For issues and questions:
- Check the Issues page
- Review the Devici API documentation
- Ensure your API credentials have proper permissions
Note: This is an unofficial MCP server for Devici. For official Devici support, please contact the Devici team.
推荐服务器

Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。