"Understanding Task Analysis, Splitting, and Execution Strategies" matching MCP servers:

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.

A server that enables executing and validating SQL queries against Google BigQuery with safety features that prevent data modifications and excessive processing.

This read-only MCP Server allows you to connect to Azure Analysis Services 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-assisted development by running and testing code directly on Databricks clusters via natural language, then deploying Databricks Asset Bundles.

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

Stateless Streamable HTTP MCP endpoint with OAuth 2.1 authentication via Cloudflare Workers, supporting PKCE, DCR, and token introspection.

Enables AI agents to discover and invoke backend tools over MCP JSON-RPC while enforcing 3-legged OAuth 2.0 identity propagation, role-based access control, and protocol transcoding to REST APIs.

Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.

Enables natural-language querying and analysis of AWS spending and model-invocation usage, including detailed breakdowns by service, region, account, day, and instance type.

Enables natural-language queries of AWS spend and Bedrock usage data, providing detailed breakdowns by service, region, account, user, instance type, and model, including cross-account cost analysis.

Enables users to query and visualize AWS spend and Amazon Bedrock usage data through natural language, including EC2 and service cost breakdowns and Bedrock usage by region, user, and model.

Enables users to query AWS spend data and Amazon Bedrock usage from CloudWatch model invocation logs through natural language. Supports detailed cost breakdowns by service, region, day, and instance type, including cross-account AWS spend retrieval.

Enables users to query AWS spending and Amazon Bedrock usage in natural language through MCP clients, with breakdowns by service, region, day, model, and user, plus optional cross-account access.

Enables users to query and analyze cloud spending, EC2 cost breakdowns, service-level spend, and model usage logs through natural-language interactions. It also supports cross-account spend retrieval when configured.

A deployable MCP server template for Cloudflare Workers that provides Google OAuth authentication and comprehensive analytics tracking of tool usage, performance metrics, and user behavior.

Enables querying AWS Cost Explorer spend data and Amazon Bedrock model invocation logs through CloudWatch in natural language. Supports EC2, Bedrock, and cross-account cost analysis via local or remote MCP transports.

Enables querying AWS spend data via Cost Explorer and Amazon Bedrock usage data from CloudWatch logs using natural language. Supports cross-account access, local and remote deployment, and integration with Claude Desktop and LangGraph agents.

Plan AWS disaster recovery budgets conversationally, comparing backup/restore, pilot light, warm standby, and active/active strategies using live Cost Explorer data.