Data Observability
Top open-source Data Observability AI systems, agents, and MCP tools.
Discover and install verified Data Observability AI systems, autonomous agent skills, and Model Context Protocol servers on AIStoreHub. Reusable, security-scanned, and ready for 1-click execution in Cursor, Claude Code, and terminal workflows.
Available AI Systems & Skills (13)
Open in Advanced FilterThe open-source context layer for your AI. Catalog your tables, topics, queues and APIs then expose real metadata to your AI agents.
The Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.
Open-source agent skills for debugging and optimizing Apache Spark workloads
Polymarket tennis trading toolkit (Python, MIT, observe-only): discover tennis markets on the Gamma API, match them to live tennis matches, watch market price vs live score, server and break point. The data layer for a Polymarket or Kalshi tennis trading bot.
Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.
Build for agents — from the AI Gateway to the entire application stack.
Run Claude Code, Gemini, Codex — or any coding agent — in a clean, isolated sandbox with sensitive data redaction and observability baked in.
The semantic layer that makes enterprise data understandable to AI agents — model entities and relations once, query through SPL/MCP/REST, and connect telemetry, services, and business objects in one object graph.
DevOps cockpit in one window: terminal with local AI, Kubernetes, SSH, databases, IDE with git, alerts, notes and KeePass. Free, open source, Linux/Windows/macOS. Рабочее место DevOps-инженера в одном окне.
A Model Context Protocol (MCP) server for Langfuse, enabling AI agents to query Langfuse trace data for enhanced debugging and observability
Open-source, self-hosted alerting for metrics, logs, and databases. Includes a built-in AI agent and MCP server.
Audit trail database for AI agents. Tamper-evident, checksum-backed decision logs with session replay and time-travel debugging to support EU AI Act Article 12 record-keeping. Drift detection, MCP, Python & TypeScript SDKs. Self-host or cloud.
Build & Monetize for Data Observability
Have you created an autonomous agent, MCP server, or Claude Code skill for Data Observability? Publish it to AIStoreHub with dual-currency checkout (USD $ + INR ₹) and earn 85–90% net revenue.