Enables AI-powered creation, configuration, and management of DevContainer environments, including building, testing, starting, stopping, and monitoring containers through natural language prompts.
Enables AI-powered creation, configuration, and management of DevContainer environments, including building, testing, starting, stopping, and monitoring containers through natural language prompts.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@DevContainer MCP Server Create a React TypeScript project with Tailwind CSS on port 3000"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A comprehensive Model Context Protocol (MCP) server that enables AI-powered DevContainer management. This server allows developers to create, configure, build, test, and modify DevContainer environments using natural language prompts through VS Code, Cursor, or any MCP-compatible editor.
Natural Language Processing: Convert plain English descriptions into valid devcontainer.json configurations
Template System: 11+ pre-built templates for popular development stacks (Node.js, Python, Go, Rust, Java, etc.)
Container Management: Build, test, start, stop, and monitor DevContainers using DevContainer CLI
Live Modification: Update existing configurations based on natural language requests
Status Monitoring: Real-time container health and configuration status
Multi-Editor Support: Compatible with VS Code, Cursor, Claude Desktop, and other MCP clients
CLI Tool: Standalone command-line interface for direct usage
Related MCP server: devcontainer-mcp
Node.js 18+
Docker or Podman
DevContainer CLI: npm install -g @devcontainers/cli
npm install -g devcontainer-mcp-servergit clone https://github.com/Siddhant-K-code/mcp-devcontainer.git
cd mcp-devcontainer
npm install
npm run buildAdd to your VS Code settings.json:
{
"mcp.servers": {
"devcontainer": {
"command": "devcontainer-mcp-server",
"args": [],
"env": {}
}
}
}Add to your Cursor configuration:
{
"mcp": {
"servers": {
"devcontainer": {
"command": "devcontainer-mcp-server"
}
}
}
}Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or equivalent:
{
"mcpServers": {
"devcontainer": {
"command": "devcontainer-mcp-server",
"args": []
}
}
}Generate a React TypeScript project:
"Create a React TypeScript project with Tailwind CSS on port 3000"Python Django with PostgreSQL:
"Python Django web application with PostgreSQL database and Redis cache"Go microservice:
"Go API server with Gin framework, PostgreSQL database, and Docker support on port 8080"Full-stack MEAN application:
"MEAN stack development environment with MongoDB, Express, Angular, and Node.js"The system automatically detects technologies and generates appropriate configurations:
Languages: JavaScript, TypeScript, Python, Go, Rust, Java, PHP, Ruby
Frameworks: React, Angular, Vue, Express, Django, Flask, Spring, Rails
Databases: PostgreSQL, MySQL, MongoDB, Redis, SQLite, Elasticsearch
Tools: Docker, Git, development tools, VS Code extensions
Ports: Automatic port detection and forwarding
generate_devcontainerGenerate DevContainer configuration from natural language.
Parameters:
prompt (required): Natural language description
workspaceRoot (optional): Workspace path (default: ".")
baseTemplate (optional): Template to start from
build_devcontainerBuild container from configuration.
Parameters:
workspaceRoot (optional): Workspace path (default: ".")
configPath (optional): Custom config path
rebuild (optional): Force rebuild (default: false)
test_devcontainerTest container functionality.
Parameters:
workspaceRoot (optional): Workspace path (default: ".")
testCommands (optional): Custom test commands array
list_templatesShow available templates.
Parameters:
category (optional): Filter by category
modify_devcontainerModify existing configuration.
Parameters:
workspaceRoot (optional): Workspace path (default: ".")
modifications (required): Desired changes description
get_devcontainer_statusCheck container status.
Parameters:
workspaceRoot (optional): Workspace path (default: ".")
nodejs-typescript: Node.js with TypeScript support
python: Python with common packages and debugging
go: Go development with standard tooling
rust: Rust environment with Cargo and debugging
java: Java with Maven/Gradle support
php: PHP with Composer and debugging
ruby: Ruby with Rails support
react: Modern React development stack with TypeScript and Vite
mean-stack: MongoDB, Express, Angular, Node.js
docker-compose: Multi-service development
universal: Multi-language development environment
Each template includes:
Appropriate base image and runtime
Language-specific tools and debuggers
Recommended VS Code extensions
Common port forwarding
Package manager setup commands
The package includes a standalone CLI tool for direct usage:
devcontainer-mcp-cli generate "React TypeScript app with Tailwind CSS"devcontainer-mcp-cli build --workspace . --rebuilddevcontainer-mcp-cli test --command "npm test" --command "npm run lint"devcontainer-mcp-cli templates --category backenddevcontainer-mcp-cli status --workspace .devcontainer-mcp-cli modify "add Redis support and port 6379"DevContainer CLI not found:
npm install -g @devcontainers/cliDocker not running:
Ensure Docker Desktop is running
Check Docker daemon status: docker info
Build failures:
Check devcontainer.json syntax
Verify base image availability
Review build logs for specific errors
Permission issues:
Ensure Docker has proper permissions
Check file system permissions for workspace
"No suitable template found":
Try with a more specific prompt
Use list_templates to see available options
Specify a base template explicitly
"DevContainer configuration not found":
Generate configuration first with generate_devcontainer
Check .devcontainer/devcontainer.json exists
"Build timeout":
Check internet connection for image downloads
Consider using lighter base images
Increase timeout if needed for large images
The server implements the Model Context Protocol specification:
Tool registration with complete schemas
Proper request/response handling
Error responses in MCP format
Text content responses
All tools return structured responses with:
Success/failure status
Detailed output and error messages
Reasoning for configuration choices
Generated configurations in JSON format
Comprehensive error handling for:
Invalid configurations
Build failures
CLI availability issues
File system errors
Network timeouts
Run the test suite:
npm testRun with coverage:
npm run test:coverageTest specific components:
npm test -- config-generator.test.ts
npm test -- template-manager.test.ts
npm test -- devcontainer-manager.test.tssrc/
├── index.ts # Main MCP server
├── config-generator.ts # Natural language processing
├── devcontainer-manager.ts # Container operations
├── template-manager.ts # Template management
├── cli.ts # CLI tool
└── __tests__/ # Test suitenpm run build # Compile TypeScript
npm run dev # Development mode
npm run start # Production mode
npm run lint # Code lintingEdit src/template-manager.ts
Add template configuration to the templates array
Include appropriate metadata (languages, frameworks, category)
Add tests for the new template
Update documentation
Update language patterns in config-generator.ts
Add framework detection patterns
Map to appropriate VS Code extensions
Create or update templates as needed
Add test cases
We welcome contributions! Please see our contributing guidelines:
Fork the repository
Create a feature branch
Make your changes with tests
Ensure all tests pass
Submit a pull request
Install dependencies: npm install
Run tests: npm test
Build project: npm run build
Test CLI: npm run cli -- --help
MIT License - see LICENSE file for details.
DevContainer CLI for container management
Model Context Protocol for the protocol specification
VS Code DevContainers for the container standards
Build DevContainer from configuration
| Name | Required | Description | Default |
|---|---|---|---|
| workspaceRoot | No | Workspace root path | . |
| configPath | No | Custom configuration file path | |
| rebuild | No | Force rebuild without cache |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Build' implies a potentially time-consuming or resource-intensive operation, but the description doesn't mention execution time, side effects (e.g., creating container images), error handling, or any constraints like permissions or system requirements. It adds minimal context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, making it easy to parse. However, it could be more front-loaded by immediately clarifying the tool's scope or differentiating it from siblings, but as-is, it's appropriately sized for its limited content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of building a DevContainer (which can involve Docker, dependencies, and runtime setup), no annotations, and no output schema, the description is incomplete. It lacks details on what the build process entails, expected outputs (e.g., success/failure states), or how it interacts with siblings, leaving significant gaps for an agent to operate effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters (workspaceRoot, configPath, rebuild) with clear descriptions. The description adds no additional meaning about parameters—it doesn't explain how 'configuration' relates to 'configPath' or default behaviors, nor does it provide usage examples or constraints beyond what's in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Build DevContainer from configuration' states a clear verb ('Build') and resource ('DevContainer'), but it's vague about what 'from configuration' entails—it doesn't specify whether this refers to a default configuration, a custom file, or something else. It also doesn't distinguish this tool from siblings like 'generate_devcontainer' or 'modify_devcontainer', leaving ambiguity about their different roles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'generate_devcontainer' (likely for creating configs) and 'modify_devcontainer' (likely for updating existing ones), there's no indication of prerequisites, typical workflows, or exclusions, leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Generate devcontainer.json from natural language description
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | Natural language description of the development environment | |
| workspaceRoot | No | Workspace root path | . |
| baseTemplate | No | Optional template to start from |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool generates a file but doesn't disclose whether it overwrites existing files, requires specific permissions, has rate limits, or what the output looks like. For a tool that likely creates or modifies configuration files, this lack of detail is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function. It is front-loaded with the core purpose and has no unnecessary words, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of generating configuration files and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'devcontainer.json' is, how the generation works, error handling, or return values. For a tool with no structured output and behavioral unknowns, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters. The description adds no additional meaning beyond what the schema provides, such as examples of natural language prompts or how the baseTemplate interacts with generation. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate devcontainer.json from natural language description'. It specifies the verb ('generate') and resource ('devcontainer.json'), and distinguishes it from siblings like 'modify_devcontainer' or 'build_devcontainer'. However, it doesn't explicitly differentiate from 'list_templates' or 'test_devcontainer' in terms of scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when to choose this over 'modify_devcontainer' or 'build_devcontainer', or any exclusions. The agent must infer usage from the name and context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get DevContainer status and information
| Name | Required | Description | Default |
|---|---|---|---|
| workspaceRoot | No | Workspace root path | . |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'gets' information, implying a read-only operation, but doesn't specify whether it requires specific permissions, what happens if the DevContainer isn't found, or if there are rate limits. The description adds minimal behavioral context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Get DevContainer status and information'. It's front-loaded with the core action and resource, with no wasted words. However, it could be slightly more specific to improve clarity without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 optional parameter, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on usage context, behavioral traits, or output format. For a simple read operation, this might suffice, but it doesn't fully leverage the opportunity to guide the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'workspaceRoot' documented as 'Workspace root path' with a default of '.'. The description doesn't add any parameter-specific details beyond what the schema provides, but since there's only one parameter and schema coverage is high, the baseline is appropriately met without needing extra compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get DevContainer status and information' states a clear verb ('Get') and resource ('DevContainer status and information'), but it's somewhat vague about what specific information is retrieved. It doesn't differentiate from sibling tools like 'list_templates' or 'test_devcontainer' that might also provide status-related information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'build_devcontainer', 'test_devcontainer', and 'modify_devcontainer', there's no indication whether this is for checking current state, verifying configurations, or other specific contexts. No explicit when/when-not statements or alternative references are included.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List available DevContainer templates
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Filter templates by category |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('List') but doesn't describe traits like whether this is a read-only operation, if it requires authentication, what the return format looks like, or any rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and every part earns its place, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one optional parameter, no output schema), the description is minimally adequate. However, with no annotations and multiple sibling tools, it lacks context on usage scenarios and behavioral details. It's complete enough for a basic list operation but could benefit from more guidance in this server context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'category' documented as 'Filter templates by category'. The description doesn't add any meaning beyond this, such as examples of categories or how filtering works. With high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('available DevContainer templates'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its siblings like 'generate_devcontainer' or 'get_devcontainer_status', which might also involve template operations, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'generate_devcontainer' and 'get_devcontainer_status', there's no indication of whether this is for browsing templates, selecting them for use, or other contexts. It lacks explicit when/when-not statements or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Modify existing DevContainer configuration
| Name | Required | Description | Default |
|---|---|---|---|
| workspaceRoot | No | Workspace root path | . |
| modifications | Yes | Natural language description of desired changes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Modify' implies mutation, it doesn't specify whether this requires specific permissions, what happens to existing configurations, whether changes are reversible, or potential side effects. The description lacks essential behavioral context for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that directly states the tool's purpose. There's zero wasted language or unnecessary elaboration, making it efficiently front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what constitutes a 'DevContainer configuration', what types of modifications are supported, what the tool returns, or error conditions. Given the complexity of configuration modification, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description doesn't add any meaningful semantic context beyond what's in the schema - it doesn't explain how modifications are applied, what format the natural language description should use, or provide examples of valid modifications.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Modify') and target resource ('existing DevContainer configuration'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'generate_devcontainer' or 'build_devcontainer' which might also affect configurations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'generate_devcontainer' (likely for creation) and 'modify_devcontainer' (for updates), there's no indication of prerequisites, appropriate contexts, or when to choose one over another.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Test DevContainer functionality
| Name | Required | Description | Default |
|---|---|---|---|
| workspaceRoot | No | Workspace root path | . |
| testCommands | No | Custom test commands to run |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It vaguely implies testing but doesn't specify what gets tested (e.g., configuration, runtime), whether it's destructive, requires permissions, or has side effects like modifying files.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, though it lacks detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what testing involves, expected outcomes, or error handling, leaving significant gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description adds no meaning beyond the schema, such as explaining how 'testCommands' interact with default tests or what 'workspaceRoot' path format is expected.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Test DevContainer functionality' is a tautology that restates the tool name without specifying what testing entails. It lacks a clear verb-resource combination and doesn't distinguish from sibling tools like 'build_devcontainer' or 'get_devcontainer_status'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or exclusions, leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Each tool has a clearly distinct purpose with no ambiguity: building, generating, getting status, listing templates, modifying, and testing DevContainers. The descriptions reinforce these distinct roles, making misselection unlikely.
All tools follow a consistent verb_noun pattern (e.g., build_devcontainer, generate_devcontainer) with snake_case throughout. This predictability aids agent understanding and tool selection.
Six tools are well-scoped for a DevContainer management server, covering key operations without bloat. Each tool earns its place by addressing a specific aspect of the DevContainer lifecycle.
The tool set provides complete CRUD/lifecycle coverage for DevContainers: creation (generate/build), reading (get status, list templates), updating (modify), and testing. No obvious gaps exist for the stated purpose.
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