[](https://npmjs.org/package/@yepcode/mcp-server)
[](https://www.npmjs.com/package/@yepcode/mcp-server)
[](https://github.com/yepcode/mcp-server-js/actions)
[](https://smithery.ai/server/@yepcode/mcp-server)
## What is YepCode MCP Server?
An MCP ([Model Context Protocol](https://modelcontextprotocol.io/introduction)) server that enables AI platforms to interact with [YepCode](https://yepcode.io)'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](https://cursor.sh) or [Claude Desktop](https://www.anthropic.com/news/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).
### Remote Approach using SSE Server
1. Sign up to [YepCode Cloud](https://cloud.yepcode.io)
2. Get your MCP Server URL from your workspace under: `Settings` > `API credentials`.
3. Add the following configuration to your AI platform settings:
```typescript
{
"mcpServers": {
"yepcode-mcp-server": {
"url": "https://cloud.yepcode.io/mcp/sk-c2E....RD/sse"
}
}
}
```
### Local Approach
#### Required Environment Variables
- `YEPCODE_API_TOKEN`: Your YepCode API token. How to obtain:
1. Sign up to [YepCode Cloud](https://cloud.yepcode.io)
2. Get your API token from your workspace under: `Settings` > `API credentials`
#### Using NPX
Add the following configuration to your AI platform settings:
```typescript
{
"mcpServers": {
"yepcode-mcp-server": {
"command": "npx",
"args": ["-y", "@yepcode/mcp-server"],
"env": {
"YEPCODE_API_TOKEN": "your_api_token_here",
}
}
}
}
```
#### Using Docker
1. Build the container image:
```bash
docker build -t yepcode/mcp-server .
```
2. Add the following configuration to your AI platform settings:
```typescript
{
"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](https://github.com/modelcontextprotocol/inspector), which you can run with the following command:
```bash
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.
```typescript
// Input
{
code: string; // The code to execute
options?: {
language?: string; // Programming language (default: 'javascript')
comment?: string; // Execution context
settings?: Record; // 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.
```typescript
// 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"
}
}
}
}
```
### Environment Management
#### set_env_var
Sets an environment variable in the YepCode workspace.
```typescript
// 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.
```typescript
// Input
{
key: string; // Name of the variable to remove
}
```
### 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](https://yepcode.io/docs/processes/tags)).
There will be a tool for each exposed process: `run_ycp_` (or `run_ycp_` if tool name is longer than 60 characters).
#### run_ycp_
```typescript
// 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.
```typescript
// 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](LICENSE) file for details.