"Artifact Hub" matching MCP servers:

Enables LLMs to search, preview, and query data assets from ICRISAT's federation-first data hub, supporting CSV, Excel, and Word files with SQL access via DuckDB.

The artifact store for AI agents. Every output your agents produce — persisted, retrievable, shareable. Across runs, sessions, and tools. Session/agent metadata, content-hash dedup, and expiring share links; available on npm (@artifacta-mcp/mcp) and PyPI (artifacta-mcp).

A TypeScript MCP server for financial data aggregation that connects AI assistants to SEC EDGAR filings, XBRL statements, FRED economic indicators, and real-time market data.

DC Hub is the live Model Context Protocol layer for data-center and energy infrastructure. AI agents call 92 tools across 24,600+ facilities for land+power, grid, interconnection, fiber, and Capacity Source — with as_of timestamps. Connect: https://dchub.cloud/connect · Docs: https://dchub.cloud/ai-agents · Endpoint: https://dchub.cloud/mcp · Pro $99/mo.

Enables querying and managing SAP Cloud Platform Integration resources such as packages, integration flows, message processing logs, security material, and artifact lifecycle through the CPI OData v2 API.

Enables agents to read and stage geospatial datasets via Geo Hub, with read-only and controlled staging tools.

Aurekai MCP exposes 89 native akai_\* runtime operators to any MCP-compatible host, covering the full Aurekai binary family — API gateway, artifact inspection, proof bundle export, semantic embedding, batch queuing, entity detection, compression, and more. Zero external dependencies; runs locally via npx -y @aurekai/mcp.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

An open-source MCP server that aggregates Taiwan public data sources (data.gov.tw, TWSE, MOEA, CWA, etc.) and exposes them through the Model Context Protocol, enabling AI agents to query Taiwan data with a single configuration line.

Provides real-time US power grid intelligence and carbon intensity data to enable carbon-aware AI compute scheduling across major grid regions. It allows users to monitor energy generation and optimize workloads based on renewable energy availability and grid load forecasts.

MCP server that turns operator-authorized local or synthetic source records into auditable research briefs, with every finding linked to exact excerpts and hashes. Exposes a single build_research_brief tool over deterministic, no-network stdio.

Exposes a sovereign SQL database to MCP clients, enabling querying, table creation, insertion, and CSV import/export.

Central source of truth for all client data. Syncs every connected platform on a schedule, normalizes it into one client workspace, and serves it to MTOS and AI agents over MCP.

Enables AI agents to perform read-only data hub queries including table listing, schema details, distinct values, and row-limited SELECT/aggregation, while rejecting free SQL.

Enables querying a unified database of items from Gmail, Notion, Linear, and Google Calendar through MCP tools, including filtered lookups, stats, and natural-language questions.

Enables AI assistants like Claude to interact with Databricks workspaces through a secure MCP server running on Databricks Apps. Supports custom prompts and tools using the Databricks SDK.

Enables complete StreamSets Control Hub integration through conversational AI, allowing users to manage data pipelines, monitor jobs, and interactively build new pipelines with 44 tools across 9 StreamSets services. Features persistent pipeline builder sessions that let users create complete ETL workflows through natural language conversations.

This server exposes a Microsoft Fabric Data Agent as a native MCP tool, allowing clients to query the agent for KPIs, financial data, and other quantified project intelligence via natural language.

Compares weekly work reports against original data to identify incorrect values, missing items, and narrative inconsistencies, providing verification results to users.

Enables AI assistants to interact with Hadoop Hue for executing SQL queries using Hive, SparkSQL, or Impala and managing HDFS files. It supports directory browsing, file transfers, and exporting query results to CSV through the Model Context Protocol.