"A guide to finding data in public databases" matching MCP servers:

An MCP server that gives AI assistants the ability to connect to, query, profile, and monitor data sources — turning any LLM into an interactive data engineering copilot.

Enables access to SORACOM IoT platform data including Harvest sensor data, file storage, SoraCam camera footage/events, and SIM statistics through authenticated API calls.

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.

MCP server that unifies real-time telemetry from industrial systems into a single queryable interface, enabling production visibility, anomaly detection, and operational insights.

Enables AI clients to investigate data engineering workflows by exposing tools for job status, logs, schema lookup, read-only SQL, and searching documentation/incidents, along with resources and prompts for ETL failure analysis.

Enables searching for relevant tables and retrieving data from Microsoft Sentinel's data lake using natural language, supporting security hunting scenarios like password-spray detection and impossible travel checks.

Enables Claude Code to query fleet telemetry data for device health summaries, anomaly detection, capacity breach forecasts, and incident history via narrow MCP tools.

Connect AI assistants to live Meta Ads, GA4, and Google Search Console data. 100% local, credentials machine-locked and encrypted. Supports Claude Desktop, Cursor, Windsurf, Cline, and more.

Enables LLM clients to access governed data platform metrics and schema descriptions through exactly three read-only, authenticated, validated, bounded, and audited tools.

Provides comprehensive statistical analysis tools for industrial data including time series analysis, correlation calculations, stationarity tests, outlier detection, causal analysis, and forecasting capabilities. Enables data quality assessment and statistical modeling through a FastAPI-based MCP architecture.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

An MCP server that emits OpenTelemetry traces, metrics, and logs to OTLP endpoints in various formats. It includes tool-mimicry profiles to generate realistic traffic resembling common tools like nginx, postgres, and AWS Lambda for testing and demonstration purposes.

A minimal MCP server that exposes health-check and server information tools over stdio or HTTP, and can be containerized and deployed to IBM Code Engine.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

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

Enables MCP clients to triage SOC alerts while enforcing a trust firewall across retrieval, memory, and privileged actions. It exposes tools for alerts, logs, memory, and alert actions, with defenses that refuse risky operations in the presence of attacker-controllable content.

Enables state-aware Terraform/OpenTofu plan evaluation against live AWS topology and CloudWatch telemetry, detecting reliability blast radius and FinOps waste before merge.

Provides an interface to access Google Analytics Data API through Model Context Protocol (MCP), allowing users to retrieve reports and realtime data from Google Analytics 4 properties.

Enables read-only access to NORA dashboard data from Upstash Redis, covering OKRs, initiatives, KPIs, and financial summaries. It allows users to query and analyze business performance metrics and organizational alignment through standardized MCP tools.