"Attribution and Contribution Analysis in Data Science and Economics" matching MCP servers:

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.

Read-only MCP server for querying ClickHouse (product telemetry) and Elasticsearch (download analytics), built for Percona VISTA.

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

Enables MCP hosts like ChatGPT and Claude to query data platform metadata, explore schemas and tables, inspect SQL explain plans, and monitor DAG and ETL status through standardized tools.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

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

Enforces identity-based access control and audit logging for MCP servers, letting you grant fine-grained tool permissions to users and systems while failing secure by default.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

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

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

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.

Provides an MCP-native operational interface for diagnostics, explainability, regression checks, and operational memory on data-system internals like PostgreSQL and Databricks toy engines.

Enables AI clients to automatically investigate dbt test failures, trace root cause through BigQuery lineage, and generate plain-English incident reports.

Web analytics and AI session replay for agents: visitors, breakdowns, funnels, goals, revenue attribution, and AI-found site issues. Connects to the hosted Flowsery MCP server.

Enables AI assistants to query per-pattern log cost attribution, investigate cost spikes and incidents, and surface savings opportunities in plain English. It exposes the 10x platform's tools for log analysis, savings estimation, pattern mitigation, and event retrieval, with read-only demo mode available without an API key.

Connects AI assistants to cloud and SaaS logs via Tailpipe, enabling natural language querying and analysis of log data.

Monitors and analyzes Precision Time Protocol (PTP) systems in OpenShift clusters, enabling configuration analysis, real-time log monitoring, and health checks.

Enables interaction with the Bigeye Data Observability platform to query data quality issues, analyze data lineage and dependencies, track AI agent data access patterns, and perform root cause analysis for data issues.

Provides agent-native analytics and logging for coding agents, enabling product analytics, error logging, and deploy attribution through an MCP handoff.

Provides tools to search, query, and visualize Prometheus metrics, returning results in JSON format for AI analysis.