NeuroDock Chronometric runs on your own machine — the client starts it, so there is no endpoint to ping. 85 installs a week from pypi. Last commit 22 Jun 2026.
Externalises time-of-day, session boundaries, and break prompts for time-blind users.
We read the source, 3 d ago · rules 995398eba69f
Found in continuous integration, deployment or infrastructure files, or in a neighbouring package of the same monorepo. None of this is installed when you add the server: it describes how the project is built and released. We list it because a leaked key in a build pipeline is still a real problem, but it is not something this server does on your machine.
"HKCU\\Software\\Microsoft\\Windows\\CurrentVersion\\Run",
subprocess.run(
const out = execFileSync(cmd, args as string[], {
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
Today is the operative word: we check NeuroDock Chronometric every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add neurodock-mcp-chronometric -- uvx neurodock-mcp-chronometric
{
"mcpServers": {
"neurodock-mcp-chronometric": {
"command": "uvx",
"args": [
"neurodock-mcp-chronometric"
]
}
}
}
[mcp_servers.neurodock-mcp-chronometric]
command = "uvx"
args = ["neurodock-mcp-chronometric"]
{
"mcpServers": {
"neurodock-mcp-chronometric": {
"command": "uvx",
"args": [
"neurodock-mcp-chronometric"
]
}
}
}
{
"servers": {
"neurodock-mcp-chronometric": {
"type": "stdio",
"command": "uvx",
"args": [
"neurodock-mcp-chronometric"
]
}
}
}
List datasets, schemas, run APL queries, and use prompts for exploration, anomalies, and monitoring.
Read Tick clients, projects, tasks, users and time entries; log and edit time entries.
Process management and monitoring for AI agents with strict security boundaries
Query real user session replay data: tapes, transcripts, error/rage-click filters, alerts.
Production telemetry for NestJS apps: traces, errors, regressions, jobs and alerts.
Analytics for founders: traffic, search, ad spend, revenue and retention per product.
Production errors and incidents for your agent: stack traces, breadcrumbs, likely causes, triage.
MCP server providing Prometheus metrics access and PromQL query execution for AI assistants
Answers built from our own checks of this server.