"Adding functionality to large language models" matching MCP servers:

Enables users to generate and execute InfluxDB queries using natural language commands in Korean. Supports querying metrics like CPU usage, memory status, and system monitoring data through conversational interface.

A remote Model Context Protocol server acting as middleware to the Sentry API, allowing AI assistants like Claude to access Sentry data and functionality through natural language interfaces.

An interface that allows large language models like Claude to interact with ActivityWatch time tracking data through the Model Context Protocol, enabling queries about application usage, browsing history, and productivity patterns.

MCP Server for notify to telegram / weixin

Enables interaction with Datadog APIs through automatically generated tools from Postman collections. Supports monitoring operations, log management, metrics submission, and other Datadog functionality through natural language.

Enables large language models to directly access Tencent Cloud Log Service for log search, metric queries, and alarm management without code.

An MCP server that enables Large Language Models to retrieve, analyze, and query metric data from Prometheus databases through pre-defined routes.

Archived MCP server for PostgreSQL health monitoring; functionality merged into pg-dash.

Enables benchmarking of Large Language Model APIs by measuring performance metrics such as generation throughput, prompt throughput, and Time To First Token (TTFT) with configurable concurrency levels and parameters.

A production-ready Model Context Protocol (MCP) server for seamless integration between Wazuh SIEM and Large Language Models (LLMs).

A Model Context Protocol (MCP) server that integrates with the MISP (Malware Information Sharing Platform) to provide threat intelligence capabilities to Large Language Models.

Enables AI assistants to query domain expiration data from domain-monitor.io, with tools for listing domains, checking expiry, and adding new domains.

A Model Context Protocol server that enables Large Language Models like Claude to query New Relic logs and metrics using NRQL queries.

Enables interaction with Jira Service Management Operations alerts and on-call schedules, including searching alerts, reading notes and activity logs, acknowledging, closing, annotating, adding responders, and querying current and next on-call rotations.

An MCP server for AI-powered log analysis that enables parsing, searching, and debugging across nine log formats directly within Claude. It features automated error extraction, sensitive data scanning, and streaming support for large log files.

MCP plugin that alerts you when AI token usage is wasteful. Fires warnings, errors, and alerts on large outputs, verbose logs, and repetitive history, auto-suppressing noise to keep your context lean.

This server acts as a MCP bridge to interact with the Cribl REST API. It allows AI models or other MCP clients to query and manage Cribl configurations.

MCP server that exposes plugin crash reports from a crash reporting site to Claude, enabling querying and managing crash data via tools like listing frequent crashes, searching, adding comments, and managing plugins.

Alephant MCP server for AI cost control, BYO-key routing, 50+ providers, and 320+ models.

MCP server for log file analysis. Gives LLMs the ability to efficiently analyze large log files without loading them into context.