F
licenseNot graded
qualityC
maintenanceExposes the automated feature engineering LangGraph agent as MCP tools, enabling dataset profiling, feature planning, and feature code execution through MCP-compatible hosts.
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gx-mcp-server
by davidf9999
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TDQS
A3.8/5.0
Scored across 7 tools
Disambiguation5/5
Each tool addresses a distinct concern: health/version, data loading, suite/expectation management, and validation execution/result retrieval. There is no overlap between run_checkpoint and get_validation_result, as one performs the validation and the other retrieves its output.
Naming Consistency5/5
All tools follow a snake_case verb_noun pattern (run_checkpoint, get_validation_result, load_dataset, create_suite, add_expectation, get_version), with 'ping' as the only exception but it is a standard health-check name. The convention is uniform and predictable.
Tool Count5/5
Seven tools is well within the ideal range for a focused MCP server. Each tool serves a necessary function for the core workflow of building and running data validation, with no redundancy or scope creep.
Completeness3/5
The set covers the primary workflow (load data, create suite, add expectation, run checkpoint, get result), but lacks read operations for existing suites or expectations, and has no update/delete capabilities. Agents cannot discover or manage existing validation assets without extending the surface.
Maintenance
ActivityInactive
ResponsivenessNo issues