"Exploring Sentiment Analysis with Google NLP" matching MCP servers:

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

Enables AI agents to query Google Analytics 4 data, including listing accounts and properties, running historical and real-time reports with customizable metrics and dimensions.

Enables natural language queries of the Chrome UX Report API to fetch Core Web Vitals (LCP, INP, CLS, FCP, TTFB), compare form factors, benchmark pages against site averages, and analyze up to 40 weeks of performance trends.

Collects page performance metrics using Playwright, CDP, and Lighthouse, and returns a normalized PerformanceReport.

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

Enables AI assistants to search Elasticsearch logs, retrieve log details, analyze service health, scan local codebases for APIs, and create Kibana dashboards.

Provides tools and context for interacting with Google Cloud services, enabling natural language management of billing, monitoring, logging, IAM, Spanner, and more.

Enables AI assistants to query, search, and analyze logs across Google Cloud Platform projects. It supports advanced filtering by severity or resource type and provides detailed log entry retrieval and project listing capabilities.

MCP server that reports AI agent costs (tokens, latency, dollars) with per-tenant isolation via OAuth, and includes an ADK agent for natural-language queries.

Enables natural language analysis of network packet captures, including protocol detection, flow analysis, and security threat identification, integrated with AI assistants.

Enables querying and exploring KairosDB time-series data through natural language, including range/absolute queries, aggregations, last values, metric and tag listing, and health checks.

Read-only MCP server for exploring and searching OpenSearch clusters, enabling log analysis, index exploration, and query execution.

Enables data observability operations with the Sifflet platform. Supports exploring assets, monitors, incidents, generating monitor-as-code YAML from descriptions, and performing impact analysis.

An AI-powered server that provides rapid debugging of server logs with actionable fixes in under 30 seconds, featuring real-time monitoring and root cause analysis through Google Gemini integration.

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.

Enables MCP-compatible agents to interact with Grafana instances for searching, creating, and updating dashboards, exploring logs via Loki, querying datasources, managing alerts, incidents, and on-call shifts, and accessing observability data.

Enables AI assistants to interact with Google Cloud Platform services for log analysis and root cause investigation. Provides tools to query Cloud Logging, detect error patterns, and perform real-time log streaming across multiple GCP projects.

Enables diagnosis of Google Cloud Platform logs using Gemini AI via MCP tools, fetching logs from Cloud Logging for issue analysis and root cause identification.

Enables querying and managing Azure Log Analytics workspaces using KQL (Kusto Query Language). Supports executing queries, managing saved queries, and exploring workspace tables and schemas with Service Principal authentication.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.