Wassette
Wassette: A security-oriented runtime that runs WebAssembly Components via MCP
What is Wassette?
Wassette is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to wassette: a security-oriented runtime that runs webassembly components via mcp
Wassette: A security-oriented runtime that runs WebAssembly Components via MCP
This server falls under the Security and Developer Tools categories on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Wassette: A security-oriented runtime that runs WebAssembly
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx wassetteConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Wassette
Wassette is a security-oriented MCP runtime built by Microsoft that executes WebAssembly (Wasm) components in isolated sandboxes, exposing their capabilities as MCP tools to AI agents like Claude Code, GitHub Copilot, Cursor, and Gemini CLI. Components are distributed as OCI artifacts from registries like GitHub Container Registry, and each component runs in a Wasmtime sandbox with browser-grade isolation — preventing access to the host filesystem, network, or environment outside what the component explicitly declares. It is designed for scenarios where you want to extend AI agents with custom tools but cannot afford to run arbitrary native code with full host privileges.
Prerequisites
- Linux or macOS (Windows support available via the installation guide)
- curl available in your shell for the one-liner installer
- An MCP-compatible AI client: Claude Code, GitHub Copilot (VS Code), Cursor, or Gemini CLI
- Internet access to pull WebAssembly component artifacts from OCI registries (e.g., ghcr.io)
Install Wassette
Run the official install script to download the Wassette binary for your platform. The script installs to a standard location on your PATH.
curl -fsSL https://raw.githubusercontent.com/microsoft/wassette/main/install.sh | bashVerify the installation
Confirm that wassette is installed and available by checking the version.
wassette --versionConfigure your MCP client to use Wassette
Add Wassette as an MCP server in your AI client's configuration. Wassette acts as the runtime — you point your client at it and then load components on demand.
{
"mcpServers": {
"wassette": {
"command": "wassette",
"args": ["serve"]
}
}
}Load a WebAssembly component via OCI URI
Ask your AI agent to load a component from an OCI registry. Wassette downloads, verifies, and runs it in an isolated Wasmtime sandbox, then exposes its tools to the agent.
Use the component's capabilities
Once loaded, the component's tools are available to the AI agent. In the time-server example, you can ask for the current time and Wassette relays the query to the sandboxed Wasm component.
Wassette Examples
Client configuration (Claude Code)
Configure Claude Code to use Wassette as the MCP runtime for WebAssembly components:
{
"mcpServers": {
"wassette": {
"command": "wassette",
"args": ["serve"]
}
}
}Prompts to try
Interact with Wassette and WebAssembly components via natural language:
- "Please load the time component from oci://ghcr.io/microsoft/time-server-js:latest"
- "What is the current time?"
- "Load a calculator component and compute 2567 * 48"
- "What WebAssembly components are currently loaded?"
- "Unload the time component and confirm it is no longer available"Troubleshooting Wassette
wassette command not found after running the install script
The install script places the binary in a directory that should be on your PATH, but you may need to restart your shell or run source ~/.zshrc (or ~/.bashrc). Check the script output for the install path and add it to your PATH manually if needed.
OCI component pull fails with 'manifest not found' or authentication error
Public components from ghcr.io should be accessible without authentication. For private registries, authenticate first using docker login or the relevant OCI tool, as Wassette respects the local credential store.
Component loads but its tools are not visible in the AI client
After loading a component, ask the AI client to refresh its tool list or restart the MCP connection. Some clients cache the tool manifest at connection time and need a reconnect to pick up newly loaded tools.
Frequently Asked Questions about Wassette
What is Wassette?
Wassette is a Model Context Protocol (MCP) server that wassette: a security-oriented runtime that runs webassembly components via mcp It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Wassette?
Follow the installation instructions on the Wassette GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Wassette?
Wassette works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Wassette free to use?
Yes, Wassette is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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