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 real-time system monitoring and automation through MCP protocol with SSE transport, integrating with n8n workflows to check system health, query logs, and retrieve metrics from ABC system APIs. Supports natural language queries in Vietnamese and English for seamless system administration.
Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.
A locally-hosted MCP (Model Context Protocol) server that gives Claude real tools to debug Docker containers — fetch logs, inspect memory/CPU, and run diagnostic commands inside a container, all from a chat with Claude Desktop.
A pre-action risk gate for AI agents. Your agent calls the forecast tool before any irreversible action — send email, run SQL, make a payment, delete a file — and gets a risk score (0–100) and a GO / CONFIRM / STOP verdict in a few seconds.
A FastMCP server that provides LLMs with structured access to Scalene's CPU, GPU, and memory profiling for Python applications. It enables automated performance analysis, bottleneck identification, and optimization suggestions through natural language interactions in supported IDEs.
Enables reading and analyzing Cloudflare Workers logpush data stored in R2 buckets. Supports searching logs with filters, viewing statistics, accessing errors, and browsing logs by date and environment.
Zero-config MCP server that gives AI coding assistants a real-time diagnostic snapshot of your local dev environment. Detects framework, running services, recent errors, git state, and provides a health diagnosis in one call.
Cirdan maps and watches the live infrastructure your agent session can reach — Docker, Kubernetes, cloud, IaC, and telemetry — then exposes it over MCP. It fingerprints the environment, builds a dependency graph, detects incidents, and can run evidence-backed actions. It inherits the session's own access and never escalates beyond it.
Enables AI agents to manage a Canonical Landscape estate, including inventory, alerts, patching, and script execution, with built-in safety layers to prevent accidental destructive actions.
Enables natural language interaction with SumoLogic for log management and analytics, with contextual awareness through a configuration file that maps your environment.
A read-only MCP server for querying telemetry data from configurable backends. Provides tools to list sources, describe schemas, run bounded queries, and compute aggregates.
A safety-first MCP server for managing UniFi networks, exposing 17 tools for telemetry, diagnostics, and guarded mutations with dry-run previews and confirm requirements.