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stdout-mcp-server
Ein MCP -Server, auf dem jeder Prozess Stdout -Protokolle in die Einbeziehung von Konsolenprotokollen aus NodeJS -Programmen einbeziehen kann
3 years
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stdout-mcp-server
A Model Context Protocol (MCP) server that captures and manages stdout logs through a named pipe system. This server is particularly useful for:
- Capturing logs from multiple processes or applications and making them available for debugging in Cursor IDE.
- Monitoring application output in real-time and providing a MCP interface to query, filter, and analyze logs
How It Works
-
The server creates a named pipe at a specific location (
/tmp/stdout_pipe
on Unix/MacOS or\\.\pipe\stdout_pipe
on Windows) -
Any application can write logs to this pipe using standard output redirection. For example:
your_application | tee /tmp/stdout_pipe # or
your_application > /tmp/stdout_pipe
-
The server monitors the pipe, captures all incoming logs, and maintains a history of the last 100 entries
-
Through MCP tools, you can query, filter, and analyze these logs
System Requirements
Before installing, please ensure you have:
- Node.js v18 or newer
Installation Options
Option 1: Installation in Cursor
- Open Cursor and navigate to
Cursor > Settings > MCP Servers
- Click on "Add new MCP Server"
- Update your MCP settings file with the following configuration:
name: stdout-mcp-server
type: command
command: npx stdout-mcp-server
Option 2: Installation in other MCP clients
Installation in other MCP clients
For macOS/Linux:
{
"mcpServers": {
"stdio-mcp-server": {
"command": "npx",
"args": [
"stdio-mcp-server"
]
}
}
}
For Windows:
{
"mcpServers": {
"mcp-installer": {
"command": "cmd.exe",
"args": ["/c", "npx", "stdio-mcp-server"]
}
}
}
Usage Examples
Redirecting Application Logs
To send your application's output to the pipe:
# Unix/MacOS
your_application > /tmp/stdout_pipe
# Windows (PowerShell)
your_application > \\.\pipe\stdout_pipe
Monitoring Multiple Applications
You can redirect logs from multiple sources:
# Application 1
app1 > /tmp/stdout_pipe &
# Application 2
app2 > /tmp/stdout_pipe &
Querying Logs
Your AI will use the get-logs
tool in your MCP client to retrieve and filter logs:
// Get last 50 logs
get-logs()
// Get last 100 logs containing "error"
get-logs({ lines: 100, filter: "error" })
// Get logs since a specific timestamp
get-logs({ since: 1648675200000 }) // Unix timestamp in milliseconds
Features
- Named pipe creation and monitoring
- Real-time log capture and storage
- Log filtering and retrieval through MCP tools
- Configurable log history (default: 100 entries)
- Cross-platform support (Windows and Unix-based systems)
Named Pipe Locations
- Windows:
\\.\pipe\stdout_pipe
- Unix/MacOS:
/tmp/stdout_pipe
Available Tools
get-logs
Retrieve logs from the named pipe with optional filtering:
Parameters:
-
lines
(optional, default: 50): Number of log lines to return -
filter
(optional): Text to filter logs by -
since
(optional): Timestamp to get logs after
Example responses:
// Response format
{
content: [{
type: "text",
text: "[2024-03-20T10:15:30.123Z] Application started\n[2024-03-20T10:15:31.456Z] Connected to database"
}]
}
License
MIT License
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Reviews

user_2KSuCwmB
As a dedicated user of the ???? Kubernetes AI Management System, I've found it incredibly efficient for managing and deploying AI workloads on Kubernetes. The system optimizes resource utilization and simplifies complex tasks seamlessly. Kudos to hariohmprasath for creating such an innovative solution! Highly recommended for AI-driven projects. Check it out at https://mcp.so/server/k8s-ai/hariohmprasath.