"A server for data engineering tasks, GPU clustering, nomad setup, and data pipeline management" matching MCP servers:

A sovereign, high-speed, local-first Big Data Ingestion, Filtering, and Analytical Pipeline Orchestrator.

Enables AI clients to investigate data engineering workflows by exposing tools for job status, logs, schema lookup, read-only SQL, and searching documentation/incidents, along with resources and prompts for ETL failure analysis.

Enables AI agents to inspect a mock data platform locally via SQLite, using read-only tools for schemas, row counts, freshness, queries, and pipeline status without cloud credentials.

An MCP server that gives AI assistants the ability to connect to, query, profile, and monitor data sources — turning any LLM into an interactive data engineering copilot.

An MCP server with 66+ tools for data engineering, enabling AI assistants to interact with Kafka, databases, AWS, data pipelines, infrastructure, and more.

The only MCP server providing structured Chinese fashion supply chain intelligence for AI platforms. No equivalent data source exists in the MCP ecosystem. Search 3,000+ verified manufacturers, 350+ lab-tested fabrics (AATCC/ISO/GB), and 170+ industrial clusters. Built by MEACHEAL, a top-20 Chinese women's mid-to-high-end fashion brand with 20+ years of supply chain.

Enables AI agents to discover, request access to, and query data products in Data Mesh Manager, enforcing governance policies while retrieving business data from platforms like Snowflake and Databricks.

Connect any AI to PostgreSQL, MySQL, or SQL Server — 24 dialect-aware tools for query, schema, optimization, and more.

Bootstrap MCP server for future data exploration and querying across multiple databases, currently only provides a hello_world tool with no actual data connectivity.

Enables Claude or any MCP-capable assistant to explore and query a small business's sales, payments, invoices, and expenses through read-only SQL tools, while personal-data columns and write operations are refused by the database policy.

MCP server for querying work checkpoints and storing finalized timesheet reports in SQLite.

Enables MCP clients to ask bilingual data questions, inspect database tables and schemas, and execute validated read-only SQL through exposed tools.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

Enables read-only access to public U.S. healthcare market-intelligence datasets, including catalogs, schemas, metadata, checksums, and artifact URLs. It supports CMOs, analysts, researchers, and AI agents in discovering and consuming governed market observations without patient-level data.

Enables LLM clients to access governed data platform metrics and schema descriptions through exactly three read-only, authenticated, validated, bounded, and audited tools.

Enables running SQL warehouse validation checks through natural-language questions in MCP clients, while reusing the same logic for automated pipeline and CI/CD runs.

Enables agents to discover, inspect, and query municipal open datasets from data.seattle.gov through Socrata SODA2, with bounded reads, aggregates, and reference guidance.

Model Context Protocol (MCP) server providing access to 155 normalized Japanese public open datasets (10.16M+ records) including GEPS procurement, healthcare, land prices, and DuckDB SQL.

An MCP server that lets an LLM query a DuckDB warehouse of EuroLeague and EuroCup basketball data in natural language, offering tools for player and team stats, shot charts, boxscores, and fantasy draft analysis without contacting upstream APIs.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.

MCP server providing AI assistants access to Polish public registries (KRS, CEIDG) and statistical data (GUS BDL) for querying companies, sole proprietorships, and regional statistics.

Enables agents to explore a database safely and read-only through three tools — list_tables, describe_table, and run_query — served over stdio. Queries are guarded by lexical validation, a capped LIMIT, a read-only SQLite connection, and an authorizer with a timeout.

Lets AI agents and developers inspect and query local MySQL, Redis, and MongoDB instances over STDIO or authenticated loopback HTTP, with read-only defaults and allowlisted non-production writes that require explicit opt-in. Production connections always reject writes, and database-enforced read-only accounts are recommended.

An MCP server for internal data platforms that enables search, viewing, tracing, and read-only querying of business assets like dashboards, metrics, and events.

An MCP server for interacting with SQL Server databases that enables schema inspection, record counting, and paginated data retrieval. It provides tools to explore table structures and fetch specific records while enforcing safety limits on data volume.

Enables answering questions about Ukrainian open data from the data.gov.ua CKAN portal by searching datasets, inspecting resource schemas, and running read-only SQL aggregates over a single tabular resource. Every data-backed answer is computed from retrieved data and returned with machine-readable provenance, and unsupported or unanswerable requests are refused rather than guessed.

Provides tools for interacting with SQL Server databases, enabling users to retrieve paginated table data, inspect schemas, and count records. It features enforced pagination and secure configuration options to manage database operations efficiently through natural language.

An MCP server for data reconciliation between MySQL and Snowflake, enabling LLM agents to validate data integrity during migrations and ETL processes.

Profiles authorized local datasets into inspectable Data Context for AI assistants, with optional local model-assisted interpretation.

Exposes data query and auto-insights (anomaly detection) as MCP tools. Enables AI agents to query metrics, list columns, and get data insights directly from pandas.