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Glama
rbmuller

scherlok

by rbmuller
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
SCHERLOK_CONNECTIONYesDatabase connection string for Scherlok MCP server

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_tablesA

List the tables visible to the configured warehouse connection.

Returns the table names (capped) and a total count. Use this to discover what can be profiled before calling investigate or watch.

investigateA

Profile tables and store them as the baseline for future anomaly checks.

Pass tables to limit to specific tables, or omit to profile everything visible. The first profile of a table establishes its baseline; no anomalies are reported here. Run watch later to detect drift.

watchA

Profile tables and detect anomalies against the stored baseline.

Returns the anomalies found (type, severity, message per table), capped. Pass tables to limit scope, or omit to watch everything. Tables with no prior baseline are profiled silently (their baseline is set for next time).

statusA

Report the current monitoring state.

Returns the connection target (password redacted), how many tables the connection can see, and how many anomalies were recorded in the last 30 days. A quick health glance without profiling anything.

historyA

Return anomalies recorded in the last days days (capped).

Reads from the local profile store — does not re-profile the warehouse.

checkA

Run a watch over all tables and return a CI-style pass/fail gate.

fail_on is "critical" (default — fail only on CRITICAL) or "warning" (stricter — fail on WARNING or worse). Mirrors scherlok ci. Returns passed plus the severity counts the decision was based on.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.1/5.0

Scored across 6 tools

Disambiguation5/5

Each tool has a distinct purpose: check is CI pass/fail, history retrieves past anomalies, investigate profiles and sets baseline, list_tables discovers tables, status gives health, watch detects anomalies against baseline. No overlap in functionality.

Naming Consistency4/5

All tool names are short, imperative verbs except for 'history' which is a noun. However, the naming is consistent in style and easy to understand, with no mixing of conventions like camelCase or snake_case.

Tool Count5/5

6 tools is appropriate for a data quality monitoring server. Each tool covers a necessary step in the workflow (discovery, profiling, detection, CI, history, status) without unnecessary bloat.

Completeness4/5

The tool set covers the core monitoring lifecycle: table discovery, profiling, baseline setting, anomaly detection, CI check, history, and status. Minor gaps exist, such as no tool for resetting baselines or managing anomalies, but these are manageable.

Maintenance

ActivityActive
ResponsivenessWithin a week

Resources