"Guidance for writing a conclusion for a long text" matching MCP servers:

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

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 that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

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.

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

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.

An MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.

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.

MCP server that integrates with VictoriaMetrics vmanomaly API to enable AI-assisted anomaly detection, model management, and configuration generation.

Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

Provides tools to search Splunk logs, inject test data, and send triage emails, enabling AI-driven incident investigation.

Enables AI-powered debugging through structured logging with pattern recognition and intelligent analysis. Allows applications to write structured logs and receive actionable debugging insights based on error patterns and frequency analysis.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Streams live progress from long-running MCP tool calls to any connected client. Instrument a tool call with mcp-telemetry-sdk, and telemetry_subscribe pushes its steps, logs, cost, and completion over notifications/progress — no polling, and a job started in one session can be watched from a different one.

Portkey Admin API control-plane MCP server with Prisma AIRS interoperability guidance.

RunBeacon is an MCP server that turns long-running local and SSH commands into tracked jobs. It provides event-driven monitoring, a live dashboard, and a resident daemon for reliable execution and cancellation.

A Model Context Protocol (MCP) server that exposes lnav log file analysis capabilities to AI assistants, specifically optimized for Kvaser Plain Text Log Frame CAN bus log processing.

Enables interaction with FortiAnalyzer JSON-RPC APIs for system health, ADOM/device inventory, alerts, reports, LogView searches, and documented long-tail read endpoints.