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pgEdge/ai-dba-workbench
A PostgreSQL monitoring system that combines traditional and AI-based monitoring for instances v14+ including Supabase and Amazon RDS.
It provides a unified environment for monitoring and managing PostgreSQL v14+ instances, including Supabase and Amazon RDS, by combining traditional monitoring with an optional AI agent for diagnosis and resolution. The system combines an MCP server with a web UI and data collector, supporting both cloud LLMs like Claude and local models from Ollama to function in air-gapped environments.
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sources
Claims below include README evidence. A matching quote or worker agreement does not establish that a claim is correct. Category majority among 2 workers. Version 1.
A PostgreSQL monitoring system that combines traditional and AI-based monitoring for instances v14+ including Supabase and Amazon RDS.
The pgEdge AI DBA Workbench is a unified environment for monitoring and management of any PostgreSQL v14+ instance, including Supabase and Amazon RDS, with an optional AI agent.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
It provides a unified environment for monitoring and managing PostgreSQL v14+ instances, including Supabase and Amazon RDS, by combining traditional monitoring with an optional AI agent for diagnosis and resolution.
The pgEdge AI DBA Workbench is a unified environment for monitoring and management of any PostgreSQL v14+ instance, including Supabase and Amazon RDS, with an optional AI agent.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
The system combines an MCP server with a web UI and data collector, supporting both cloud LLMs like Claude and local models from Ollama to function in air-gapped environments.
The architecture supports switching between cloud-connected LLMs like Claude and locally hosted models from Ollama. This design ensures similar levels of functionality in air-gapped or secure environments.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Monitors PostgreSQL instances to catch anomalies before they become outages and guides diagnosis and resolution.
The Workbench watches every instance, catches anomalies before they become outages, and walks through diagnosis and resolution step by step.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Combines an MCP server, web-based user interface, and data collector for querying and managing clusters.
The Workbench combines a Model Context Protocol (MCP) Server with a web-based user interface and data collector.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Uses an Alerter component to evaluate metrics against thresholds and perform AI-powered anomaly detection.
The Alerter evaluates collected metrics against thresholds and AI-powered anomaly detection to generate alerts.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Includes a Collector that monitors PostgreSQL servers and stores metrics in a centralized datastore.
The Collector monitors PostgreSQL servers and stores metrics in a centralized datastore.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Allows users to query, analyze, and manage distributed clusters using natural language and intelligent automation.
Users can query, analyze, and manage distributed clusters using natural language and intelligent automation.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Exposes pgEdge tools and data sources like Spock replication status and operational metrics to language models.
The Workbench exposes pgEdge tools and data sources such as Spock replication status, cluster configuration, and operational metrics to language models.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Provides a web-based client interface for interacting with the AI DBA Workbench.
The Client provides a web-based user interface for the AI DBA Workbench.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Provides MCP tools and resources for interacting with PostgreSQL systems.
The Server provides MCP tools and resources for interacting with PostgreSQL systems.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Monitors PostgreSQL instances to detect anomalies early and guides users through diagnosis and resolution steps.
The Workbench watches every instance, catches anomalies before they become outages, and walks through diagnosis and resolution step by step.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Enables querying, analysis, and management of distributed PostgreSQL clusters via natural language and automation.
Users can query, analyze, and manage distributed clusters using natural language and intelligent automation.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Supports switching between cloud LLMs and local models like Ollama for functionality in air-gapped or secure environments.
The architecture supports switching between cloud-connected LLMs like Claude and locally hosted models from Ollama.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Collects metrics from PostgreSQL servers and stores them in a centralized datastore for analysis.
The Collector monitors PostgreSQL servers and stores metrics in a centralized datastore.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Evaluates metrics against thresholds and uses AI-powered anomaly detection to generate alerts.
The Alerter evaluates collected metrics against thresholds and AI-powered anomaly detection to generate alerts.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Provides a web-based user interface for interacting with the AI DBA Workbench.
The Client provides a web-based user interface for the AI DBA Workbench.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Provides MCP tools and resources to interact with PostgreSQL systems.
The Server provides MCP tools and resources for interacting with PostgreSQL systems.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
Exposes tools and data sources like replication status and cluster configuration to language models.
The Workbench exposes pgEdge tools and data sources such as Spock replication status, cluster configuration, and operational metrics to language models.
Quote matched the README or GitHub description at extraction. Same claim and quote from 1 worker(s). Interpretation not reviewed by a maintainer.
network-monitoring · ai-ml