How does Signal Agent ๐จ classify failure events?
It uses a keyword-based analysis pipeline that recalculates severity independently from the source, then classifies into categories like database, network, security, or service failure.
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Basic information
MCP server / agent concept for signals interpretation and processing
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"signals-agent": {
"command": "uv",
"args": [
"venv"
]
}
}
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A production-ready MCP server and client system that transforms raw failure events into actionable intelligence through automated classification, severity analysis, and response recommendations. It is designed for operations teams and developers handling incident response.
Install via git clone and use just compile/just sync. Run the demo with just run, the server with just run-server, or the agent with just run-agent. Test interactively using the MCP Inspector via npx @modelcontextprotocol/inspector uv run python server/server.py.
It uses a keyword-based analysis pipeline that recalculates severity independently from the source, then classifies into categories like database, network, security, or service failure.
Python 3.8+, the `uv` package manager, and the `just` command runner. The MCP official SDK and Pydantic are used internally.
Currently stdio for local development and testing. HTTP (streamableโhttp) transport is planned for future distributed deployments.
Run the server standalone with `just run-server` and connect via MCP Inspector using `npx @modelcontextprotocol/inspector uv run python server/server.py`.
MIT License โ see the LICENSE file in the repository.
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