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"Understanding Prompts or Prompt Engineering" matching MCP servers:

  • F
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    Provides full execution and management capabilities for Microsoft Fabric Data Engineering workloads, including notebooks, pipelines, Lakehouses, and Spark jobs. It enables users to trigger runs, monitor status, manage workspace items, and configure job schedules through natural language.
  • A
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    MCP server that provides AI assistants direct access to the Apache Zeppelin REST API for data engineering workflows, enabling notebook and paragraph management, execution, and interpreter control.
    14
    24
    2
    MIT
  • A
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    A hybrid Fivetran MCP server with 23 native tools for common data engineering tasks and two universal tools (search/execute) that unlock all 161 Fivetran REST API endpoints.
    25
    MIT
  • F
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    Enables AI to analyze and transform data using fusion algorithms with statistical, machine learning, or hybrid methods. Provides seamless data format conversion and enhanced analytical capabilities through the Model Context Protocol.
    2
  • A
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    Enables AI applications to integrate with Tableau through tools, resources, and prompts for querying data, exploring content, and retrieving visualizations from Tableau workbooks and datasources.
    11,978
    321
    Apache 2.0
  • A
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    Connects MCP clients to databases like Snowflake, BigQuery, and Databricks through Alkemi's data platform, enabling natural language database queries with proper schema understanding and metadata management for consistent team-wide access.
    14
    4
    MIT
  • A
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    Converts JSON data and system prompts to and from TOON (Token-Oriented Object Notation) format, reducing token usage by 30-60% when interacting with LLMs while preserving data structure.
    MIT
  • A
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    Enables AI applications to integrate with Tableau through developer primitives including tools, resources and prompts. Supports querying data from datasources, exploring content like workbooks and views, and retrieving visualizations using the Tableau REST API.
    11,978
    Apache 2.0
  • F
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    Integrates with Narrative's Data Collaboration Platform, enabling AI assistants to search attributes, list datasets, manage access rules, and execute NQL queries via MCP tools and prompts.
  • A
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    Parses unstructured US contact strings into structured name and address components. Supports automatic detection of input type (name, address, or contact) and optional enhancement using a US street database.
    BSD 3-Clause
  • A
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    quality
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    Expose IBKR account data, portfolio positions, orders, executions, contracts, and market data snapshots via MCP to Claude or Codex.
    8
    MIT
  • A
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    Transforms high-level business intents into structured Data Product Requirement Prompts through AI-powered conversational refinement. Guides users through clarifying questions to gather comprehensive requirements for automated Business Intelligence dashboard generation.
    1
    Apache 2.0
  • A
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    Provides deterministic tools for understanding, transforming, and verifying structured data via MCP, enabling rule inference from examples and verification of transformed records.
    MIT
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    quality
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    Executes SQL queries via ConnectorX and streams results to CSV or Parquet files, supporting multiple databases and optional token counting for CSV output.
    1
    MIT