"Information about community managers or community management" matching MCP servers:

A community-maintained MCP server for interacting with PagerDuty accounts, enabling management of incidents, services, schedules, and event orchestrations through MCP-enabled clients.

A read-only MCP server for OpenObserve Community Edition that works over the REST API. Provides tools for searching logs, traces, stream schemas, and dashboards - no Enterprise license required.

An MCP server for Security Onion Community Edition that provides 21 read and write tools for SOC operations, including event querying, alert management, detection tuning, PCAP retrieval, and agent enrollment, without requiring a Pro license.

Enables AI assistants to query Cisco ThousandEyes v7 API for network monitoring data including tests, agents, alerts, dashboards, and test results (network, page-load, web-transactions, path visualization) for faster troubleshooting through natural language.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

A Python-based MCP server that enables querying Cisco's Meraki Dashboard API to discover, monitor, and manage Meraki environments.

Enables plant operators to query alarm data, asset information, trends, correlations, and operator recommendations through 14 tools, forming a core part of a multi-MCP enterprise operations copilot.

An MCP server that provides comprehensive monitoring and management capabilities for Teradata Workload Management (WLM), enabling tasks like performance troubleshooting, emergency throttling, and scheduled maintenance through 41 tools and 39 resources.

A Model Context Protocol server that provides access to Observe API functionality, enabling LLMs to execute OPAL queries, manage datasets/monitors, and leverage vector search for documentation and troubleshooting runbooks.

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.

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The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.

A local MCP server for read-only SNMPv2c queries, providing snmp_get and snmp_walk tools over stdio with CIDR-based community string configuration.

Provides Claude with access to Shodan for IP address lookups, service discovery, and vulnerability scanning, allowing users to query information about hosts, count results, and check API usage.

Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.

Enables integration with Datadog APIs to monitor and retrieve information about monitors, metrics, dashboards, logs, events, and incidents through the Model Context Protocol.

MCP server for the FortiMonitor v2 monitoring API. 241 tools across 33 modules covering server management, outage monitoring, maintenance windows, metrics, notifications, cloud monitoring, SNMP, dashboards, reporting, and more. Unofficial community project, not affiliated with Fortinet. Python, MIT license, Docker and local deployment supported.

Enables AI assistants to query and fetch error and performance monitoring data from AppSignal through the Model Context Protocol. Supports searching and retrieving detailed information about application errors and performance samples with flexible filtering options.

Enables comprehensive system monitoring and diagnostics through 18 tools that provide detailed information about CPU, memory, disk usage, network interfaces, running processes, battery status, hardware details, and temperature monitoring. Allows users to query system information and performance metrics through natural language interactions.