"Information about backend development or backend systems" matching MCP servers:

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

MCP servers for real-time development monitoring and interactive pair programming.

Enterprise AI operator evaluation MCP server. 27 tools (22 read + 5 write) for measuring, benchmarking, diagnosing, and interv ening on how human operators use AI tools across 5 canonical metrics.

Enables AI agents to investigate backend incidents by executing runbooks that gather evidence from observability and storage systems.

Unified observability gateway for AI agents — one MCP server for Prometheus, Loki, and any backend.

Sigma detection rule writing, validation, and pySigma-based multi-backend conversion (Splunk, Elastic, Wazuh, Kibana) via 3 MCP tools and 3 Claude Code skills, backed by a 61-rule production corpus across 11 MITRE ATT\&CK tactic categories.

Enables LLMs to analyze and manage DBOS workflows, including introspection, workflow management, and authentication, to help debug applications in development or production.

Governed reverse-proxy operations for Traefik, Caddy, and HAProxy — backend-health, cert-expiry, 5xx, and route-conflict RCA, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

Enables interaction with Beszel system monitoring tool to query system and container statistics, manage alerts, and monitor infrastructure through its PocketBase backend.

Get information about the current operating environment

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

A Model Context Protocol server that provides secure database access to PostgreSQL through Kysely ORM, enabling natural language interaction with PostgreSQL databases. It offers 40+ MCP tools for querying, schema inspection, diagnostics, and Java backend monitoring.

A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.

Enables read-only observability of Windows systems, exposing CPU, memory, storage, service, and health information through Model Context Protocol tools.

Provides Claude with access to Shodan for IP address lookups, service discovery, and vulnerability scanning, allowing users to query information about hosts, count results, and check API usage.

Lets AI agents inspect Kubernetes clusters in plain English, exposing read-only tools for pods, deployments, services, events, and logs, with mock and real backend support.

Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.

Enables Alexa+ to answer plain-English questions about a home network using live diagnostics such as ping latency, bandwidth, connected devices, and interface health, with optional local or AWS Bedrock LLM reasoning and safe service restart tools.

Enables tracing of synthetic events through a toy Redis Streams + Postgres ingestion pipeline, answering questions about which events were dropped, duplicated, delayed, or are in flight, plus overall pipeline health. It also supports first-class fault injection and reconciles observed pipeline state against independently recorded producer ground truth to expose real loss or silent failures.

Enables read-only access to operations and telemetry data across 12 domains through 45 agent tools, including asset inventory, metrics, outages, incidents, and platform settings, with support for AWS SigV4-signed live access and a fixture-based mock mode that runs without a backend.