Provides unified project context and monitoring capabilities including project health metrics, build diagnostics, Git integration, and infrastructure validation to initialize development sessions with comprehensive project information.
Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.
Provides LLM agents with read-only access to Cloudera Edge Flow Manager (EFM) for MiNiFi edge agents. Enables fleet health monitoring, flow inspection, and deployability validation through GET-only tools.
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.
Provides tools to monitor host system health including CPU load, disk usage, and network status while enabling file system management tasks like searching and moving files. It includes built-in safety guards to prevent operations on critical system directories.
Provides intelligent OpenAI API token management with automatic switching between model tiers when usage limits are reached. It enables users to track daily token consumption, estimate costs before making calls, and manage project-specific usage data.
Enables AI agents to query Windows process, window, and console information via structured JSON instead of screenshots, reducing token usage by 94-98%.
Provides a read-only summary of Ubuntu server status including system version, resource usage, apt updates, service health, security logs, and hardware information to AI clients via MCP tools.
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.
Enables LLMs to securely manage Virtual Private Servers via SSH, with features including command execution, file operations, system monitoring, and service management.
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.
Enables centralized management and monitoring of multiple distributed worker MCP servers. Provides tools to list workers, get status of all workers, and query specific worker status.