Provides tools for DeepTempo AI SOC including findings and case management, investigation workflow orchestration, action approval workflows, and MITRE ATT&CK layer generation.
MITM proxy MCP server that intercepts and verifies AI agent tool calls, detecting fabrication, tracking costs, verifying outcomes, and inferring user satisfaction.
Enables read-only access to cookieless web analytics aggregates such as sites, visitors, pages, sources, live activity, funnels, and uptime monitoring through OAuth 2.1-secured Streamable HTTP tools.
Enables natural language Kubernetes operations, including smart resource queries, pod root-cause analysis, cross-environment diffs, and manifest generation.
Provides a scalable, containerized infrastructure for deploying and managing Model Context Protocol servers with monitoring, high availability, and secure configurations.
An MCP server that enables interaction with Google Cloud Logging API, allowing users to write, read, and manage log entries and configurations through natural language.
Uptime monitoring for websites, APIs, SSL certificates, domain expiry, ping and TCP/UDP ports. 15 tools to list, create, pause and delete monitors, pull incident timelines with error codes, and read hourly or daily uptime and response-time statistics.
Enables agents to query GPU availability across SSH hosts, find free GPUs, list hosts, and inspect fleet status using only nvidia-smi on the remote side.
MCP server for monitoring health of MCP servers, GitHub Actions, GitLab pipelines, and HTTP endpoints with health history, TLS expiry, assertions, diagnostics, and alerts.
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.
A read-only stdio MCP server that provides a generic log-querying layer for Grafana/Loki, enabling discovery, retrieval, and aggregation of logs (raw, slow, errors, volumes) through 15 tools, with hard limits on data volume and no built-in business logic.
Connects AI assistants to OpenTelemetry trace backends such as Jaeger, Tempo, Traceloop, and Datadog, enabling natural-language searching of traces and spans, error discovery, and service listing. It also provides LLM-specific analytics, including token usage aggregation, model performance comparison, and identification of the most expensive or slowest traces.
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.