Integration with Timeplus, a database for streaming data, such as Apache Kafka/Pulsar

The Seq MCP Server enables interaction with Seq's API endpoints for logging and monitoring, providing tools for managing signals, events, and alerts with extensive filtering and configuration options.

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.

Enables AI models to analyze webpage performance using the Google PageSpeed Insights API, providing real-time performance scores and improvement suggestions.

A high-performance FastAPI server supporting Model Context Protocol (MCP) for seamless integration with Large Language Models, featuring REST, GraphQL, and WebSocket APIs, along with real-time monitoring and vector search capabilities.

Provides a scalable, containerized infrastructure for deploying and managing Model Context Protocol servers with monitoring, high availability, and secure configurations.

Enables automated web accessibility scans for WCAG compliance using Playwright and Axe-core, providing visual and JSON reports with remediation guidance.

Facilitates deployment and management of services using the Model Context Protocol with a focus on high availability, scalability, and secure communication, leveraging Docker-based infrastructure, Prometheus, and Grafana for monitoring.

A Model Context Protocol server that provides LLM Agents with a comprehensive toolset for IP geolocation, network diagnostics, system monitoring, cryptographic operations, and QR code generation.

Agentic tool that looks for statistical variations in conversation structure and logs unusual events to a SQLite database. Built using the Model Context Protocol (MCP), this system is designed to be used with Claude Desktop or other MCP-compatible clients.

Enables AI assistants to check software end-of-life dates and support status using the endoflife.date API, providing accurate information on software lifecycle, security status, and upgrade recommendations in real-time.

provide access to monitor and cluster logs from datadog

Enables AI models to interact with Jira using a standardized protocol, offering full Jira REST API integration with features like optimal performance through connection pooling, error handling, and request monitoring.

Provides an interface to access and manage JIRA data through the Model Context Protocol, offering features like relationship tracking, data cleaning, and contextual insights for AI applications.

A Node.js server that integrates with pytest to facilitate the ModelContextProtocol (MCP) service tools, enabling test execution recording and environment tracking.

Server for interacting with Honeycomb observability data. This server enables LLMs like Claude to directly analyze and query your Honeycomb datasets.

MCP server for interacting with Prometheus metrics and data.

Query and interact with kubernetes environments monitored by Metoro. Look at APM, metrics, traces, profiling information with LLMs.

MCP Server for Raygun's API V3 endpoints for interacting with your Crash Reporting and Real User Monitoring applications. This server provides comprehensive access to Raygun's API features through the Model Context Protocol.

This server provides tools to inspect error reports, stacktraces, and other debugging information from your Sentry account.