#inci

A Model Context Protocol (MCP) server for interacting with DaVinci Resolve and Fusion

Mirror of

Mirror of

Run NRQL, NerdGraph, and REST v2 operations to query data, manage incidents, create synthetics, and annotate deployments — all from your MCP client. A full‑featured New Relic MCP server that goes far beyond basic NRQL. It exposes safe, typed tools for APM discovery, alert policy/incident workflows (including acknowledge), entity search and deep details, creating Synthetics Browser monitors, and New Relic REST v2 coverage for deployments and metrics with region awareness and auto‑pagination.

Read-only doctrine and example access for the Agentic AI Blueprint — the industry standard reference for safe, observable, and steerable AI agent UX. Browse and search 10 principles across principle clusters, access curated implementation examples, retrieve application guides for security and evaluation challenges, and download agent asset artifacts. 13 public tools require no credentials. Auth-gated tools for learning path and coaching context require a Firebase Bearer token.

MCP server integration for DaVinci Resolve

A Model Context Protocol (MCP) server that provides integration with PagerDuty for incident management and monitoring operations.

The Pulsetic MCP Server connects Pulsetic monitoring with AI agents and MCP-compatible tools, enabling direct access to uptime data, cron monitoring results, incident management workflows, and status page information through the Model Context Protocol (MCP). It allows teams to securely expose operational monitoring data in a structured format, making it easy to build AI-driven automation, monitoring assistants, and intelligent operational workflows without custom middleware. Core Capabilities Uptime Monitoring Access real-time and historical uptime data through AI systems. Query monitor health, availability metrics, and performance status directly from AI agents or automation workflows. Cron Monitoring Track scheduled jobs and background tasks with cron monitoring insights. Detect missed executions, delays, or failures and integrate alerts into AI-powered operational processes. Incident Management Retrieve incident history, status updates, and timelines programmatically. Automate incident analysis, reporting, and response workflows using AI tools. Status Pages Integrate public or internal status page data into AI environments. Automatically surface service status, ongoing incidents, and maintenance updates for improved transparency and communication. Use Cases AI-powered uptime and reliability monitoring Automated incident response and reporting Intelligent cron job supervision Status page automation and operational visibility Internal AI assistants for DevOps and SRE teams The Pulsetic MCP Server brings uptime monitoring and operational intelligence directly into modern AI ecosystems, enabling smarter automation, faster troubleshooting, and improved service reliability.

Your AI agent's interface to incident management. Acknowledge, escalate, page, and resolve incidents from Claude Code, Cursor, or any MCP client. Covers the full incident lifecycle: incidents, on-call, services, postmortems, and teams.

Deterministic scrap-vehicle quoting + lead submission tools for AI agents. Call get_vehicle_quote with a year/make/model to receive an indicative CAD price range; always relay the phone number and website from the response to the end user so they can complete the transaction with ScrapAutos.

Real-time status monitoring, API pricing, usage limits, and incident data for 50+ AI services including ChatGPT, Claude, Gemini, Grok, and Perplexity. Ask your agent: "Is the Claude API having issues?" or "What's the current GPT-4o pricing?" Independent probe data — not delayed provider status pages. Agents can also report failures they encounter via report_incident, contributing to a shared intelligence layer.

An open-source Model Context Protocol (MCP) server for the InvGate Service Desk / Service Management API. Exposes 96 tools across 11 domains — incidents (create, update, comment, reassign, approvals), users & groups, knowledge base, custom fields, assets/CIs, workflows, triggers, breaking news and time tracking. Read-only by default. Write access is opt-in via granular profiles: `support` (incidents + time tracking, KB stays read-only) or `full` (adds Knowledge Base writes). Backward compatible, fail-fast on misconfiguration, with optional OpenTelemetry instrumentation. Install: `uvx invgate-service-desk-mcp`. Published on PyPI and listed in the official MCP registry.

MCP-native AI SRE. Aient exposes your production OpenTelemetry problems, traces, and logs over the Model Context Protocol, plus an AI remediation loop that opens a reviewed GitHub fix PR and verifies in production (reopening on regression). Tools: list_problems, get_problem, query_traces, detect_anomalies, request_problem_remediation. Remote streamable-HTTP at https://aient.ai/mcp; auth via OAuth (scopes aient.mcp.read / aient.mcp.write). Human-in-the-loop by default. Request access at aient.ai.