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Add scala-mcp-server to Data Platforms
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@@ -851,6 +851,7 @@ Data Platforms for data integration, transformation and pipeline orchestration.
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- [1luvc0d3/metabase-mcp](https://github.com/1luvc0d3/metabase-mcp) [](https://glama.ai/mcp/servers/1luvc0d3/metabase-mcp) 📇 🏠 - MCP server connecting Claude to Metabase with 28 tools for natural language data analysis, dashboard management, SQL queries, and automated insights. Features SQL guardrails, rate limiting, and audit logging.
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- [alanpcf/brasil-data-mcp](https://github.com/alanpcf/brasil-data-mcp) [](https://glama.ai/mcp/servers/alanpcf/brasil-data-mcp) 📇 🏠 🍎 🪟 🐧 - Brazilian public data for AI agents — companies (CNPJ), addresses (CEP), banks (BACEN), national holidays — via [BrasilAPI](https://brasilapi.com.br). No auth, no API key. Install: `npx -y brasil-data-mcp`.
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- [Alessandro114/scala-mcp-server](https://github.com/Alessandro114/scala-mcp-server) [](https://glama.ai/mcp/servers/Alessandro114/scala-mcp-server) 📇 ☁️ 🍎 🪟 🐧 - Search and enrich data from 250M+ companies across 50+ countries. Company lookup by name, VAT, or ID, NACE sector search, and financial data from official EU business registries. Free tier: 50 lookups/month. Install: `npx scala-mcp-server`.
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- [antonio-mello-ai/mcp-airflow](https://github.com/antonio-mello-ai/mcp-airflow) [](https://glama.ai/mcp/servers/antonio-mello-ai/mcp-airflow) 🐍 🏠 - Manage Apache Airflow through its REST API — list DAGs, inspect DAG runs and task instances, trigger runs, and check failed-DAG and scheduler/metadatabase health. 7 tools, built with FastMCP. Install: `uvx mcp-airflow`.
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- [carrierone/verilexdata-mcp](https://github.com/carrierone/verilexdata-mcp) [](https://glama.ai/mcp/servers/carrierone/verilexdata-mcp) 📇 ☁️ - 20 structured datasets (NPI healthcare, SEC filings, OFAC sanctions, crypto whales, Polymarket signals, patents, economic indicators) via x402 pay-per-query with USDC. Free stats/sample endpoints, MCP + HTTP transport.
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- [aegis-dq/aegis-dq](https://github.com/aegis-dq/aegis-dq) [](https://glama.ai/mcp/servers/aegis-dq/aegis-dq) 🐍 🏠 🍎 🪟 🐧 - Agentic data quality framework that runs structured rules against warehouses (DuckDB, BigQuery, Athena, Databricks, Postgres), diagnoses failures with LLM root cause analysis, and proposes SQL remediations. Every LLM decision is audit-logged with cost and latency.
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