Execute any LLM-generated code in the YepCode secure and scalable sandbox environment and create your own MCP tools using JavaScript or Python, with full support for NPM and PyPI packages
An MCP (Model Context Protocol) server that enables AI platforms to interact with YepCode's infrastructure. Run LLM generated scripts and turn your YepCode processes into powerful tools that AI assistants can use directly.
YepCode MCP server can be integrated with AI platforms like Cursor or Claude Desktop using either a remote approach (we offer a hosted version of the MCP server) or a local approach (NPX or Docker installation is required).
Settings
> API credentials
.{
"mcpServers": {
"yepcode-mcp-server": {
"url": "https://cloud.yepcode.io/mcp/sk-c2E....RD/sse"
}
}
}
YEPCODE_API_TOKEN
: Your YepCode API token. How to obtain:
Settings
> API credentials
Add the following configuration to your AI platform settings:
{
"mcpServers": {
"yepcode-mcp-server": {
"command": "npx",
"args": ["-y", "@yepcode/mcp-server"],
"env": {
"YEPCODE_API_TOKEN": "your_api_token_here",
}
}
}
}
docker build -t yepcode/mcp-server .
{
"mcpServers": {
"yepcode-mcp-server": {
"command": "docker",
"args": [
"run",
"-d",
"-e",
"YEPCODE_API_TOKEN=your_api_token_here",
"yepcode/mcp-server"
]
}
}
}
Debugging MCP servers can be tricky since they communicate over stdio. To make this easier, we recommend using the MCP Inspector, which you can run with the following command:
npm run inspector
This will start a server where you can access debugging tools directly in your browser.
The MCP server provides several tools to interact with YepCode's infrastructure:
Executes code in YepCode's secure environment.
// Input
{
code: string; // The code to execute
options?: {
language?: string; // Programming language (default: 'javascript')
comment?: string; // Execution context
settings?: Record<string, unknown>; // Runtime settings
}
}
// Response
{
returnValue?: unknown; // Execution result
logs?: string[]; // Console output
error?: string; // Error message if execution failed
}
YepCode MCP server supports the following options:
run_code
tool. For example, if you want to use the MCP server as a provider only for the existing tools in your YepCode account.Options can be passed as a comma-separated list in the YEPCODE_MCP_OPTIONS
environment variable or as a query parameter in the MCP server URL.
// SSE server configuration
{
"mcpServers": {
"yepcode-mcp-server": {
"url": "https://cloud.yepcode.io/mcp/sk-c2E....RD/sse?mcpOptions=disableRunCodeTool,skipRunCodeCleanup"
}
}
}
// NPX configuration
{
"mcpServers": {
"yepcode-mcp-server": {
"command": "npx",
"args": ["-y", "@yepcode/mcp-server"],
"env": {
"YEPCODE_API_TOKEN": "your_api_token_here",
"YEPCODE_MCP_OPTIONS": "disableRunCodeTool,skipRunCodeCleanup"
}
}
}
}
Sets an environment variable in the YepCode workspace.
// Input
{
key: string; // Variable name
value: string; // Variable value
isSensitive?: boolean; // Whether to mask the value in logs (default: true)
}
Removes an environment variable from the YepCode workspace.
// Input
{
key: string; // Name of the variable to remove
}
The MCP server can expose your YepCode Processes as individual MCP tools, making them directly accessible to AI assistants. This feature is enabled by just adding the mcp-tool
tag to your process (see our docs to learn more about process tags).
There will be a tool for each exposed process: run_ycp_<process_slug>
(or run_ycp_<process_id>
if tool name is longer than 60 characters).
// Input
{
parameters?: any; // This should match the input parameters specified in the process
options?: {
tag?: string; // Process version to execute
comment?: string; // Execution context
};
synchronousExecution?: boolean; // Whether to wait for completion (default: true)
}
// Response (synchronous execution)
{
executionId: string; // Unique execution identifier
logs: string[]; // Process execution logs
returnValue?: unknown; // Process output
error?: string; // Error message if execution failed
}
// Response (asynchronous execution)
{
executionId: string; // Unique execution identifier
}
Retrieves the result of a process execution.
// Input
{
executionId: string; // ID of the execution to retrieve
}
// Response
{
executionId: string; // Unique execution identifier
logs: string[]; // Process execution logs
returnValue?: unknown; // Process output
error?: string; // Error message if execution failed
}
This project is licensed under the MIT License - see the LICENSE file for details.
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