
mcp-server-js
Enable secure, AI-driven process automation and code execution on YepCode via Model Context Protocol.
Key Features
Use Cases
README
What is YepCode MCP Server?
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.
Why YepCode MCP Server?
- Seamless AI Integration: Convert YepCode processes into AI-ready tools with zero configuration
- Real-time Process Control: Enable direct interaction between AI systems and your workflows
- Enterprise-Grade Security: Execute code in YepCode's isolated, production-ready environments
- Universal Compatibility: Integrate with any AI platform supporting the Model Context Protocol
Integration Guide
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).
For both approaches, you need to get your YepCode API credentials:
- Sign up to YepCode Cloud
- Visit
Settings
>API credentials
to create a new API token.
Remote Approach using SSE Server
- If your MCP Client doesn't support authentication headers, just use the SSE server URL that includes the API Token. Use a configuration similar to the following:
{
"mcpServers": {
"yepcode-mcp-server": {
"url": "https://cloud.yepcode.io/mcp/sk-c2E....RD/sse"
}
}
}
- If your MCP Client supports authentication headers, you can use the HTTP server URL that includes the API Token. Use a configuration similar to the following:
{
"mcpServers": {
"yepcode-mcp-server": {
"url": "https://cloud.yepcode.io/mcp/sse",
"headers": {
"Authorization": "Bearer <sk-c2E....RD>"
}
}
}
}
Local Approach
Using NPX
Make sure you have Node.js installed (version 18 or higher), and use a configuration similar to the following:
{
"mcpServers": {
"yepcode-mcp-server": {
"command": "npx",
"args": ["-y", "@yepcode/mcp-server"],
"env": {
"YEPCODE_API_TOKEN": "your_api_token_here"
}
}
}
}
Using Docker
- Build the container image:
docker build -t yepcode/mcp-server .
- Use a configuration similar to the following:
{
"mcpServers": {
"yepcode-mcp-server": {
"command": "docker",
"args": [
"run",
"-d",
"-e",
"YEPCODE_API_TOKEN=your_api_token_here",
"yepcode/mcp-server"
]
}
}
}
Debugging
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.
YepCode MCP Tools Reference
The MCP server provides several tools to interact with YepCode's infrastructure:
Code Execution
run_code
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
}
MCP Options
YepCode MCP server supports the following options:
- Disable the run_code tool: In some cases, you may want to disable the
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. - Skip the run_code cleanup: By default, run_code processes source code is removed after execution. If you want to keep it for audit purposes, you can use this option.
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,runCodeCleanup"
}
}
}
// 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,runCodeCleanup"
}
}
}
}
Environment Management
set_env_var
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)
}
remove_env_var
Removes an environment variable from the YepCode workspace.
// Input
{
key: string; // Name of the variable to remove
}
Storage Management
YepCode provides a built-in storage system that allows you to upload, list, download, and delete files. These files can be accessed from your code executions using the yepcode.storage
helper methods.
list_files
Lists all files in your YepCode storage.
// Input
{
prefix?: string; // Optional prefix to filter files
}
// Response
{
files: Array<{
filename: string; // File name or path
size: number; // File size in bytes
lastModified: string; // Last modification date
}>;
}
upload_file
Uploads a file to YepCode storage.
// Input
{
filename: string; // File path (e.g., 'file.txt' or 'folder/file.txt')
content: string | { // File content
data: string; // Base64 encoded content for binary files
encoding: "base64";
};
}
// Response
{
success: boolean; // Upload success status
filename: string; // Uploaded file path
}
download_file
Downloads a file from YepCode storage.
// Input
{
filename: string; // File path to download
}
// Response
{
filename: string; // File path
content: string; // File content (base64 for binary files)
encoding?: string; // Encoding type if binary
}
delete_file
Deletes a file from YepCode storage.
// Input
{
filename: string; // File path to delete
}
// Response
{
success: boolean; // Deletion success status
filename: string; // Deleted file path
}
Process Execution
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).
run_ycp_<process_slug>
// 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
}
get_execution
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
}
License
This project is licensed under the MIT License - see the LICENSE file for details.
Star History
Repository Owner
Organization
Repository Details
Programming Languages
Tags
Topics
Join Our Newsletter
Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.
Related MCPs
Discover similar Model Context Protocol servers

mcp
Universal remote MCP server connecting AI clients to productivity tools.
WayStation MCP acts as a remote Model Context Protocol (MCP) server, enabling seamless integration between AI clients like Claude or Cursor and a wide range of productivity applications, such as Notion, Monday, Airtable, Jira, and more. It supports multiple secure connection transports and offers both general and user-specific preauthenticated endpoints. The platform emphasizes ease of integration, OAuth2-based authentication, and broad app compatibility. Users can manage their integrations through a user dashboard, simplifying complex workflow automations for AI-powered productivity.
- ⭐ 27
- MCP
- waystation-ai/mcp

cloudflare/mcp-server-cloudflare
Connect Cloudflare services to Model Context Protocol (MCP) clients for AI-powered management.
Cloudflare MCP Server enables integration between Cloudflare's suite of services and clients using the Model Context Protocol (MCP). It provides multiple specialized servers that allow AI models to access, analyze, and manage configurations, logs, analytics, and other features across Cloudflare's platform. Users can leverage natural language interfaces in compatible MCP clients to read data, gain insights, and perform automated actions on their Cloudflare accounts. This project aims to streamline the orchestration of security, development, monitoring, and infrastructure tasks through standardized MCP connections.
- ⭐ 2,919
- MCP
- cloudflare/mcp-server-cloudflare

awslabs/mcp
Specialized MCP servers for seamless AWS integration in AI and development environments.
AWS MCP Servers is a suite of specialized servers implementing the open Model Context Protocol (MCP) to bridge large language model (LLM) applications with AWS services, tools, and data sources. It provides a standardized way for AI assistants, IDEs, and developer tools to access up-to-date AWS documentation, perform cloud operations, and automate workflows with context-aware intelligence. Featuring a broad catalog of domain-specific servers, quick installation for popular platforms, and both local and remote deployment options, it enhances cloud-native development, infrastructure management, and workflow automation for AI-driven tools. The project includes Docker, Lambda, and direct integration instructions for environments such as Amazon Q CLI, Cursor, Windsurf, Kiro, and VS Code.
- ⭐ 6,220
- MCP
- awslabs/mcp
Didn't find tool you were looking for?