"Fetching Kubernetes logs for a given pod or deployment" matching MCP servers:

Enables inspecting and managing Kubernetes clusters through MCP, including listing deployments and pods, retrieving logs and events, and scaling or restarting deployments.

A Model Context Protocol (MCP) server that provides safe, read-only access to Kubernetes resources for debugging and inspection. Built with security in mind, it offers comprehensive cluster visibility without modification capabilities.

Enables AI agents to analyze ROS2 log files across multiple nodes by merging them into a unified timeline and providing smart query tools, without requiring ROS2 installation.

MCP server for querying and analyzing logs from VMware Aria Operations for Logs, enabling log search, incident detection, and vROps correlation.

Enables safe, read-only interaction with Kubernetes clusters, allowing users to list resources and fetch logs without any create/update/delete operations.

Enables diagnosing Kubernetes clusters without creating or changing cluster objects, with tools to inspect health, workloads, events, storage, RBAC, custom resources, logs, and configuration.

MCP server for Python JSON logs

An MCP server that gives AI assistants direct access to Kubernetes clusters for pod management and network debugging (DNS, NetworkPolicy, ingress, service mesh) and correlates Dynatrace observability with OpenTelemetry self-monitoring, which automatically ships traces, metrics, and logs to Dynatrace.

Enables log analysis for Tenable Patch Management (SaaS and on-prem) by parsing, de-duplicating, and decoding server/client logs into structured verdicts, ranked issues, and known-issue fixes.

Enables AI agents to manage prompts and sessions via the ai-agent-logs API, with tools for health checks, login, listing/creating prompts, and retrieving sessions.

An MCP server that connects Claude (or any MCP compatible client) to your existing log infrastructure. Query, summarize, and trace logs in plain English across GCP Cloud Logging, AWS CloudWatch, Azure Log Analytics, Grafana Loki, and Elasticsearch without writing filter expressions or leaving your editor.

A read-only MCP server for Kubernetes that allows querying cluster information and diagnosing issues through natural language interfaces like Claude.

Enables advanced management of Kubernetes clusters through natural language interactions. Supports querying, managing, and monitoring pods, deployments, nodes, and logs across multiple contexts and namespaces.

Read-only MCP server for Elasticsearch log querying. Enables natural language search, filtering, context retrieval, and aggregation of logs.

Enables interactive Kubernetes cluster monitoring and troubleshooting through natural language queries. Users can diagnose pod issues, check service status, and investigate cluster problems using conversational AI.

Enables querying and analyzing Datadog logs through search, aggregation, and index listing.

Provides a set of read-only Kubernetes functions via an MCP server, enabling interaction with Kubernetes clusters through agents or coding assistants like GitHub Copilot.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Enables querying OpenTelemetry logs stored in OpenSearch across development and production environments. Provides tools for searching logs by various criteria including free-text Lucene queries, trace IDs, service names, error levels, and specific fields.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

An MCP server for searching and visualizing SolarWinds Observability logs, allowing users to query log data with filtering options and generate visual representations of log events over time.

Enables searching and retrieving Datadog logs through the Model Context Protocol with customizable queries, time ranges, and result limits.

Enables natural language Kubernetes cluster operations, SLO monitoring, and PromQL queries via Claude using the Model Context Protocol.

An MCP server that downloads Elasticsearch logs from Elastic Cloud via the Admin API.

Enables real-time Kubernetes cluster observability and debugging through standardized MCP interface. Provides access to pods, services, nodes, events, and includes built-in tools for cluster health analysis and issue identification.

An MCP server for retrieving and filtering logs from Mezmo with a quota-conscious design and intelligent defaults. It enables users to discover and query logs by application, level, and custom time ranges to streamline debugging while minimizing API usage.

A TypeScript MCP server for querying Shopee logs via the log platform's Mgmt API and Querymaster WebSocket flow, with config-driven service resolution and session reuse.

A read-only MCP server that lets AI clients investigate logs stored in VictoriaLogs over stdio, offering LogsQL search, UUID/stream lookups, stream and field discovery, hit aggregation, and stats queries with time-range and filtering controls. It supports bearer, basic, or anonymous auth, multi-tenant account/project IDs, and response size and timeout limits.

A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.

Enables an AI assistant to diagnose a broken application on a local Kubernetes cluster by inspecting pods, events, and logs, with server-side guardrails, least-privilege RBAC, and an audit log. It can also restart deployments in allowed namespaces only after a dry-run preview and host approval.