"How to respond to tagged messages on Slack" matching MCP servers:

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

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.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

A Model Context Protocol server that connects AI agents to IBM Concert, enabling autonomous workflow health monitoring, incident diagnosis, auto-remediation, CVE triage, and Slack alerting through natural language.

An AI-native incident response server that exposes diagnostic tools (system status, error logs, ticket creation) via MCP, enabling LLM agents to autonomously assess and respond to incidents.

Enables AI-driven incident response by connecting Claude to monitoring tools like Prometheus, Grafana, Loki, PagerDuty, and Slack for automated investigation and runbook generation.

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.

Minimal MCP server that integrates with Graylog, enabling agents to search, analyze, and inspect log messages across streams, discover fields and streams, and query multiple Graylog instances.

Exposes live industrial IoT telemetry to any MCP client, streaming simulated sensor data from a fleet of machines and detecting anomalies, with the ability to inject faults on demand.

Enables AI agents to interact with Freeplay, an ops platform for AI engineering teams, to analyze production logs, identify quality issues, iterate on prompts and agents using real data, and run experiments before deploying.

Read-only AMD GPU monitoring for Claude on Linux — VRAM, temperature, clocks, power, and running ML processes via rocm-smi.

An on-call agent for data incidents, built on a bio-inspired context protocol. It triages data quality and freshness issues using DataHub, computing severity, blast radius, and ownership from the catalogue before generating prose.

An MCP server that provides monitoring tools for Codex agents, allowing them to create and wait on conditions using commands, log files, file events, and custom probes, replacing polling loops with event-driven blocking.

Identifies resource-intensive processes on macOS across CPU, memory, and network usage, with tools for detailed process filtering and system overview.

Provides AI agents with real-time ground truth about what's actually running on the machine, including live agent sessions, listening TCP ports, loaded daemons, and system stats. It reads directly from the OS via fixed commands, ensuring agents never rely on stale docs or transcripts.

Lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things on your Cloudflare account.

Enables agents to report and query performance metrics to build a community-driven quality database for MCP tools. This server helps agents discover and select the most reliable tools based on success rates and user-reported quality scores.

Enables AI agents to query MQTT message history stored in SQLite, including topic inventories, last values, historical data, silent devices, and collector connection gaps. Supports publishing messages when write mode is enabled.