リモート MCP server

Lets an AI client access product analytics, feature flags, experiments, dashboards, and error tracking data.

Monitors websites for real-time updates and provides AI-powered change summaries and smart alerts for price drops or stock availability.

Lets an AI client query an indexed codebase for callers, change risk, health scores, tests, ownership, and cited answers.

Checks and signs every AI agent tool call before it runs, holds risky calls for human approval, and exports tamper-evident records anyone can verify offline.

Lets an AI client manage Rootly incidents, alerts, on-call schedules, and retrospectives through the Rootly API.

Provides runtime observability for AI agents by acting as a transparent proxy to track sessions, costs, and loop execution.

Lets an AI client run WinDbg crash dump triage, user-mode remote debugging, and kernel debugging through cdb.exe and kd.exe.

Allows AI agents to query and manage Zabbix monitoring data, including hosts, triggers, problems, and maintenance periods.

Connect AI assistants to Dynatrace to query observability data, analyze problems, and manage infrastructure through domain-specific skills.

Lets an AI client read Opik traces, log scores, and manage prompt versions in an LLM observability workspace.

Lets an AI client check emails and domains against known data breaches, view breach analytics, and browse breach metrics.

Lets an AI client query and manage LibreNMS network monitoring data, including devices, ports, alerts, logs and graphs.

Lets an AI client read WHOOP recovery, sleep, strain, cycle, workout and body measurement data via WHOOP's official OAuth API.

Lets AI agents look up CVEs, KEV entries, CWE weaknesses, MITRE techniques, Sigma rules, and domain or IP security posture.

Lets AI assistants interact with data warehouses to query alerts, monitor freshness, investigate schema drift, and trace data lineage.

Provides AI observability, explainability, and governance tools including drift detection, bias auditing, and LLM call monitoring.

Allows an AI client to access real-time latency, uptime, and deprecation data for over 45 AI inference APIs across different global regions.

Monitors real-time conversation health for AI agents by tracking semantic drift, information gain, and causal reachability using deterministic arithmetic.

Enables AI agents to instrument code with tracing, manage evaluations, configure guardrails, and debug failing tests within the Openlayer platform.

Records independent, dated records of AI agent and MCP server publications and provides signed receipts for verified facts.