openmetadata-mcp-server
Related Servers
Alternatives to openmetadata-mcp-server
No user-submitted related servers found.
Related Servers
AlicenseNot gradedqualityFmaintenanceOpen-source agentic schema layer. Define metrics once in YAML, query governed data from any warehouse (Snowflake, BigQuery, Databricks, PostgreSQL, DuckDB) via MCP.28Apache 2.0- AlicenseNot gradedqualityCmaintenanceEnables AI agents to query live schema, lineage, and query-context across data warehouses, dbt projects, orchestration systems, and BI tools via MCP tools.Apache 2.0
- AlicenseNot gradedqualityCmaintenanceData observability for AI agents. Query alerts, monitor freshness, investigate schema drift, and trace lineage across your data warehouse via 53 MCP tools.1MIT
- FlicenseNot gradedqualityCmaintenanceOpen-source autonomous agent swarm of 15 MCP-native AI agents for data engineering — catalog, quality, incidents, schema evolution, governance, migration, observability, ML. 212+ tools, Apache 2.0. Works with Claude Code, Cursor, ChatGPT, and any MCP client.12-
- AlicenseNot gradedqualityBmaintenanceMCP server with 32 tools for ETL ingestion, AI-generated data quality rules, AI transformations, vector search, and natural-language SQL. Works across Postgres, MongoDB, Kafka, S3/MinIO, HashiCorp Vault, and five vector stores (Qdrant, Weaviate, Milvus, Chroma, pgvector).12AGPL 3.0
- AlicenseNot gradedqualityCmaintenanceMCP server providing read-only Snowflake metadata tools (schemas, tables, queries, lineage) for agentic data pipeline generation, enabling natural-language-to-pipeline workflows with dbt, Airflow, and Great Expectations.1MIT
TDQS
Scored across 173 tools
The list/get/create/update/delete pattern per entity type makes most tools easy to tell apart, and UUID vs FQN variants are explicitly labeled in each description. A few aggregated and validation tools overlap conceptually (validate-data-contract vs run-data-contract-validation, get-table-summary vs get-table + get-lineage), but those descriptions are differentiated enough to avoid major mis-selection.
Overwhelmingly consistent: almost every tool uses lowercase snake_case with a verb-noun pattern like list-tables, get-table-by-name, and update-database. The small set of aggregate/utility tools (semantic-search, lineage-impact, quality-rollup, search-tools) deviates slightly from that pattern but still reads clearly.
173 tools is far beyond the extreme-mismatch threshold and will overwhelm agents, even with search-tools as a navigation aid. The per-entity CRUD expansion could be parameterized into a much smaller set without losing capability.
The set gives deep lifecycle coverage for most core data assets—tables, databases, schemas, dashboards, pipelines, topics, glossaries, teams, and domains—plus lineage, sample data, quality rollups, and data-contract validation. The main gaps are read-only admin surfaces (users, roles, policies, metrics, API collections, search indexes) and missing create/update for some service types, which are workable but noticeable.