GTM Data MCP
Related Servers
Alternatives to GTM Data MCP
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceEnables composable search and filtering over an enterprise data catalog, with tools for lineage, sample data, profiling, history, quality rules, and AI-driven classification.-
- FlicenseAqualityDmaintenanceExposes marketing catalogs (offers, assets, campaigns, and computed metrics) to MCP clients, enabling natural language queries and AI-driven marketing analysis.8-
- AlicenseNot gradedqualityBmaintenanceEnables natural-language setup and management of a governed digital product catalog, including schema, products, and rules, with dry-run previews, audit logging, and two-phase confirmations for destructive actions.MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to search, explore data lineage, understand business context, and generate SQL queries across an organization's data ecosystem.Apache 2.0
- AlicenseAqualityCmaintenanceEnables AI agents to autonomously manage and improve execution processes for repetitive task types by storing reusable task contexts with associated artifacts (practices, rules, prompts, learnings) and providing full-text search across historical best practices.81MIT
- FlicenseAqualityDmaintenanceProvides standardized brand guidelines and structured content templates for marketing assets like blogs, emails, and social media. It serves as a central source of truth for brand voice and strategy through an extensible file-based system.1-
TDQS
Scored across 15 tools
Several read-oriented tools overlap in scope: resolve_ownership and get_personnel_map both return responsibility relationships, and get_measurement_inventory, get_account_context, and get_record all offer relationship-rich snapshots. The descriptions generally clarify the primary focus of each tool, but an agent could still struggle to pick between them.
Tool names are overwhelmingly snake_case with a consistent gtm_ prefix and verb-first structure, e.g., get_, list_, search_, generate_, validate_. The only notable deviation is gtm_module_status, which uses a noun phrase rather than a verb_noun pattern, though it remains readable.
Fifteen tools is within a reasonable range for a broad data governance domain, and most tools serve a distinct read or validation purpose. However, the count feels slightly high because some tools could be consolidated or aligned more tightly around core entities.
The server is strong on read, search, lineage, readiness, and bulk-change validation coverage, so most query-oriented workflows are supported. However, there are no lifecycle or mutation tools: source updates can be listed but not approved/applied, records cannot be created or updated, and bulk changes can be generated and validated but not submitted. This leaves notable workflow dead ends, even if the read-only boundary is intentional.