Deployment Strategies | MCPLambda Docs

MCPLambda supports three distinct ways to deploy your Model Context Protocol servers. Each strategy is optimized for different use cases and development workflows.

1. Direct Package Flow

Best for: Rapidly deploying existing community-built servers or testing ideas without local setup.

This flow leverages our internal runtime to containerize and deploy servers directly from package manager URLs. You don’t need to write a Dockerfile or manage any build infrastructure.

Supported Protocols:

npx://@mcp/server-time
uvx://mcp-server-fetch
pip://mcp-server-gmail
go://github.com/mcp-server/go-server

How it works: MCPLambda’s backend identifies the protocol, resolves the package, and spins up a dedicated container with the required runtime environment (Node.js, Python, Go) automatically.

2. GitOps Flow

Best for: Custom server development, teams, and production-grade CI/CD pipelines.

Connect your GitHub repository directly to MCPLambda. Every push to your main branch (or a custom branch) triggers an automated build and deployment.

Workflow:

Connect your GitHub account.
Select your repository and branch.
MCPLambda’s Image Builder service automatically detects your language, builds a secure container image, and deploys it.
Future pushes automatically update your deployment.

3. Direct Image Flow

Best for: Ready-made containers available in public or private registries, or complex applications with custom system-level dependencies.

If you already have a pre-built container image, you can deploy it directly without any source code or package resolution.

Supported Registries:

Docker Hub
GitHub Container Registry (GHCR)
Amazon ECR
Google Artifact Registry

Example Source: ghcr.io/mcp-server/custom-server:v1.2.0

How it works: MCPLambda pulls the image directly from the registry and orchestrates the deployment based on your configuration (environment variables, storage, etc.).

Deployment Configuration

No matter which strategy you choose, you can configure the following for every deployment:

Transport: Standard I/O, Streamable HTTP (modern, recommended), or SSE. Regardless of the transport selected, MCPLambda provides a unique Deployment URL for you to plug into your MCP client. For stdio deployments, the platform automatically handles the proxying to a web-native endpoint.
Environment Variables: Inject API keys and configuration values securely.
Persistent Storage: Request a dedicated volume for servers that need to maintain state across restarts.
Server Profile: Choose between Small, Medium, or Large profiles based on your resource needs.

Which strategy should I use?

Scenario	Recommended Flow
Deploying a popular server from GitHub	Direct Package Flow
Developing your own custom MCP server	GitOps Flow
Deploying a proprietary, pre-built binary	Direct Image Flow
Testing a server with unique system libraries	Direct Image Flow