"Data Crawling Techniques and Tools for Financial Data" matching MCP servers:

A governed MCP server enabling LLM agents to query BigQuery, inspect GCS, trigger Airflow DAGs, and run data-quality checks with built-in security guardrails like allow-lists, cost ceilings, and audit trails.

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

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.

Provides a modular MCP server to integrate with IBM Data Intelligence services, enabling secure interaction with data intelligence capabilities via tools and skills.

Provides secure integration between MCP clients and IBM Data Intelligence services, enabling AI assistants to interact with IBM's data intelligence capabilities for data management and analytics operations.

Enables AI agents to analyze BigQuery datasets through MCP, using tools to inspect datasets and execute read-only SQL queries.

Generates and deploys Cloudera Data Engineering (CDE) Airflow jobs from ODCS data contracts, validating live table data in CDW against schema and data-quality rules without WAP staging.

Enables developers to manage Genesys Cloud Function Data Actions through natural language in Cursor, including validating, building, planning, and applying function deployments while enforcing safety controls like plan-before-apply and read-only mode.

This MCP server enables users to interact with AWS Amplify Gen2 application data through natural language, allowing AI assistants like Claude to perform operations on Amplify data models using conversational language instead of complex code.

Enables interaction with AWS Amplify Gen2 application data through natural language, allowing AI assistants to query, create, update, and delete records using conversational commands with Cognito authentication.

This read-only MCP Server allows you to connect to Azure Data Lake Storage data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

MCP server for VAST Data administration, enabling AI assistants to monitor, list, and manage VAST clusters.

Enables AI agents to query multi-cloud costs, inventory, waste, and commitments across AWS, GCP, Cloudflare, and OVH through read-only MCP tools.

Enables AI assistants to manage Coolify infrastructure including servers, applications, databases, deployments, and 80+ one-click services through 98 comprehensive tools for both cloud and self-hosted instances.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

An MCP server for managing and monitoring Docker, Docker Compose, and Kubernetes environments alongside Azure Application Insights. It enables advanced log filtering, container lifecycle management, and querying of cloud application traces and metrics.

Enables AI agents to manage Cloudera Data Visualization resources including groups, users, roles, segments, workspaces, datasets, visuals, connections, and migrations via natural language.