"Techniques for File Operations" matching MCP servers:

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

Enables secure, read-only inspection of a VPS over SSH through approved operations such as system health, disk usage, container logs, and service status, without giving the AI unrestricted shell access.

Enables AI-driven SOC investigations by providing automated Splunk querying, threat intelligence enrichment, and response actions through natural language. Includes tools for IP pivoting, lateral movement detection, and label harvesting.

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.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.

An MCP-native enterprise operations platform that unifies team management, product catalog, order processing, knowledge base, location intelligence, analytics, and DevOps monitoring into a single server accessible from any MCP-compatible AI agent.

Enables time-travel debugging for AI agent sandboxes using Firecracker microVMs, with tools for code execution, file operations, and VM snapshot/restore via MCP.

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.

Analyzes PCAP/PCAPNG network capture files to detect port scanning techniques (SYN, FIN, Xmas), classify scan patterns, and enrich suspicious IP addresses with threat intelligence data. Provides comprehensive network security analysis through natural language interactions.

A safety layer and monitoring copilot for AI agents using Splunk MCP, recording tool calls, enforcing policies, and blocking risky actions.

MCP server for managing a Ubiquiti UNAS Pro NAS, providing health monitoring, storage and disk inventory, NFS export visibility, read-only file inspection, and gated lifecycle operations via SSH and the UniFi Drive API.

An MCP server that demonstrates comprehensive observability with Sentry, OpenTelemetry, and Braintrust, providing tools for file, data, and HTTP operations along with real-time status and configuration resources.

A safe, read-only MCP server that gives Codex structured access to engineering operations evidence, with validated queries, secret redaction, and audit logging. Provides a search_logs tool for filtering logs by service, environment, severity, and time range.

Enables secure analysis of log files by listing, summarizing, and searching for error patterns, with defenses against path traversal, symlink attacks, and data leakage.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.

Enables classification of GPU workloads as training, inference, or idle from telemetry data, with tools for one-shot classification, benchmarking, and audit log verification.

8 standalone MCP servers for SMBs — Guardrails (prompt injection, PII, secrets detection), FinOps (AI cost tracking and budgets), Observability (agent tracing), Smart Router (17+ models, 9 providers), Trust Score (governance scoring 0-100), Memory (persistent agent memory), ThinkSecure (runtime security + SOC2/GDPR audit), and A2A Lite (agent-to-agent protocol). 37 tools total, TNC credits

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.

16-tool MCP server for Google PageSpeed Insights & Chrome UX Report APIs. Analyze, compare, and optimize web performance directly through Claude, Cursor, or any MCP-compatible AI client.

Model Context Protocol (MCP) server for debugging, analyzing, and diagnosing Kubernetes clusters directly from AI agents.