LightShip is answering right now. Last checked 7 min ago. Last commit 14 Sep 2026.
Governed access to production AI-agent traces in an existing ClickHouse store.
We read the source, 19 h ago · rules 3dff92dd89df
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
finalDir := filepath.Join(s.exportDir, id)
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 7 min ago.
claude mcp add lightship --transport http https://lightship-production.up.railway.app/mcp
{
"mcpServers": {
"lightship": {
"url": "https://lightship-production.up.railway.app/mcp"
}
}
}
[mcp_servers.lightship]
url = "https://lightship-production.up.railway.app/mcp"
{
"mcpServers": {
"lightship": {
"url": "https://lightship-production.up.railway.app/mcp"
}
}
}
{
"mcpServers": {
"lightship": {
"url": "https://lightship-production.up.railway.app/mcp"
}
}
}
This endpoint answered with an authorization challenge. The server is running, but it did not say what kind of credentials it expects.
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://lightship-production.up.railway.app/mcp | streamable-http | needs auth | 236 ms | 7 min ago |
Governed AI-agent memory, Evidence Ledger traces, evals, and portable context tools.
AI agent observability for production traces, natural-language insights, and improvement loops.
Structured execution trace and span logging for AI agents
Read-only access to Auralogs production logs: search logs, inspect errors, review AI analyses.
Every number in an AI answer traces back to the rows that produced it.
Production-ready RAG + MCP demo: eval-in-CI merge gate, Langfuse traces, structure-aware chunking.
Debug production issues using Shipbook logs and Loglytics error insights.
Govern model, agent, skill, and MCP workflows with policy, approvals, traces, and usage analytics.
Answers built from our own checks of this server.