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Data Platforms for data integration, transformation and pipeline orchestration.

MCP ServersBrowse all →

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    Direct access to 40+ scraping and search tools. Extract structured data from Google (Search, Maps, Trends), Amazon, Airbnb, Social Media, and any web page directly into your AI agent.
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    MIT
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    Investidor10 MCP Server: A Model Context Protocol (MCP) server for interacting with the Status Invest API. Provides tools for fetching stock data and indicators, with a layered architecture and data validation using Zod
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    MIT
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    Enables document processing through Upstage AI services including parsing various document formats, extracting structured information with custom schemas, auto-generating extraction schemas, and classifying documents into categories.
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    MIT
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    Unified MCP server for Arpe.io data tools enabling AI assistants to build, preview, and execute high-performance data commands including database export, transfer, pipeline, and migration.
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    MIT
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    Enables AI assistants to interact with security data pipelines and map data to the Open Cybersecurity Schema Framework (OCSF) through Tenzir. Provides seamless integration for processing and analyzing cybersecurity data using natural language.
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    Apache 2.0
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    Enables querying, inserting, and managing unstructured data in RawTree via SQL, JSON ingestion, and log inspection through MCP clients like Claude Code, Cursor, and Claude Desktop.
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    MIT
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    Official Talonic MCP server. Lets AI agents extract structured, schema-validated data from any document, including PDFs, scans, images, spreadsheets, and forms, directly inside the chat.
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    MIT
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    A server providing tools for querying and analyzing Teradata databases, including database management, data quality assessment, and SQL execution capabilities through an MCP interface.
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    MIT
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    Celp-MCP enables natural-language analytics over SQL, MongoDB, and Databricks warehouses through MCP-compatible clients, converting questions into multi-step database plans and returning markdown reports.
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    MIT
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    Enables AI assistants to manage CData Sync operations, including data synchronization jobs, connections, and ETL processes through stdio or HTTP transports. It provides tools for executing jobs, monitoring real-time progress via Server-Sent Events, and handling comprehensive workspace configurations.
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    MIT
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    A high-performance Model Context Protocol (MCP) server that provides seamless integration with Amazon DataZone services. This server enables AI assistants and applications to interact with Amazon DataZone APIs through a standardized interface.
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    Apache 2.0
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    Enables managing CSVBox importer sheets through MCP tools, including creating, replacing, patching, generating, validating, and scaffolding importers from any MCP-compatible client.
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    MIT
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    Enables document processing with Suparse API, extracting structured data from documents into JSON, CSV, XLSX, or Google Sheets, and supports processing single files or folders.
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    MIT
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    Production-ready MCP server for Apache DolphinScheduler. Enables AI agents to operate data workflows end-to-end with 58 tools covering DAG creation, schedule management, instance control, guided troubleshooting, serial backfills, and version rollback.
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    Apache 2.0
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    A Model Context Protocol server that lets you fetch Microsoft Clarity analytics data through Claude for Desktop or other MCP-compatible clients, with support for filtering by dimensions and retrieving various metrics.
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    MIT
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    The Token Metrics Model Context Protocol (MCP) server provides comprehensive cryptocurrency data, analytics, and insights through function calling. This server enables AI assistants and agents to access Token Metrics' powerful API for real-time crypto market data, trading signals, price predictions, and advanced analytics.
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    TypeScript
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    A unified Model Context Protocol server for data engineering and analytics that lets LLM clients query, profile, transform, and visualize data using DuckDB and PySpark, while keeping raw data out of the model's context through read-only, bounded, and audited operations.
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    MIT
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    Enables AI assistants to interact with Databar.ai's data enrichment API, allowing discovery, configuration, and execution of data enrichments across hundreds of providers using natural language.
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    MIT
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    Enables AI assistants to upload clinical documents and medical device images for health data extraction, normalization, and retrieval of structured coded results in formats such as JSON, FHIR, HL7, CSV, and Parquet.
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    264
    MIT

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