"How to automate workflows in DaVinci Resolve and Fusion" matching MCP servers:

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

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 production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Enables coding agents to read performance findings from sixty, get detailed evidence for each finding, and close or resolve them with descriptions, while also checking service telemetry and providing installation instructions.

Enables LLMs to analyze and manage DBOS workflows, including introspection, workflow management, and authentication, to help debug applications in development or production.

MCP server enabling AI agents to trace and resolve order synchronization incidents between an ERP (Odoo) and multiple marketplaces.

An MCP server for detecting retry loops and analyzing iteration patterns in agentic coding workflows, providing structured debugging intelligence to improve repair attempts.

MCP server for AI-assisted trading operations, enabling agents to diagnose and resolve FIX, OMS, and venue incidents through controlled tools and human approval.

Enables interacting with Bugsnag to investigate and resolve errors via natural language. Supports browsing organizations, projects, errors, stacktraces, and exception chains.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

Operates Rancher-managed Kubernetes through any MCP client with capability detection, generic resource access, and curated workflows, wrapped in an audit-logged, rate-limited, confirmation-guarded safety model.

Prove your SRE agent can resolve incidents before production by replaying synthetic incidents and scoring agent performance via MCP tools.

A middleware service that uses Model Context Protocol to analyze and automate Zabbix events with AI, enabling automated incident response and workflow automation through n8n integration.

Real-time observability dashboard for monitoring AI agents in multi-agent development workflows, with live WebSocket updates of tool calls, sessions, and usage statistics.

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.

Connects MCP-capable AI clients to a monitoring API to inspect cron and recurring-task checks, with opt-in mutations for pings, integrations, and check changes.

MCP server that enables querying an OpenObserve instance for logs, traces, and metrics via tools like search_logs, search_traces, get_trace, and query_metrics, supporting natural-language-driven observability workflows.

Enables AI agents to monitor and debug browser runtime errors, console logs, and page diagnostics in real time via a Chrome extension and local MCP server.

Enables Claude Code to inspect network traffic, query the DOM, read console logs, and capture WebSocket frames in Firefox.