Other MCP Server · MODEL CONTEXT PROTOCOL
amitdeshmukh stdout mcp server
An MCP server that any process can pipe stdout logs to including console logs from nodejs programs
WHAT IT CONNECTS
What amitdeshmukh stdout mcp server gives an AI Agent
- 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)
- Windows: `\\.\pipe\stdout_pipe`
- Unix/MacOS: `/tmp/stdout_pipe`
- `lines` (optional, default: 50): Number of log lines to return
- `filter` (optional): Text to filter logs by
- `since` (optional): Timestamp to get logs after
SECURITY
An MCP listing is not a security review
An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.
README
Repository documentation
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
-
The server creates a named pipe at a specific location (
/tmp/stdout_pipeon Unix/MacOS or\\.\pipe\stdout_pipeon 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
Before installing, please ensure you have:
- Node.js v18 or newer
- 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-serverFor 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"]
}
}
}To send your application's output to the pipe:
# Unix/MacOS
your_application > /tmp/stdout_pipe
# Windows (PowerShell)
your_application > \\.\pipe\stdout_pipeYou can redirect logs from multiple sources:
# Application 1
app1 > /tmp/stdout_pipe &
# Application 2
app2 > /tmp/stdout_pipe &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- 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)
- Windows:
\\.\pipe\stdout_pipe - Unix/MacOS:
/tmp/stdout_pipe
Retrieve logs from the named pipe with optional filtering:
Parameters:
lines(optional, default: 50): Number of log lines to returnfilter(optional): Text to filter logs bysince(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"
}]
}MIT License
COMMUNITY