"Maintaining Consistent Behavior in System Prompts" matching MCP connectors:

Find your AI agent's likely failure mode, get runtime settings, and clarify ambiguous prompts.

Give AI coding agents access to your Vynix visual feedback, bug reports, and AI diagnosis.

Third-party signed reads of how an AI agent behaved: drift, vows, and the town it works in.

Uptime and website monitoring for AI agents. Query monitor status, incidents, heartbeats, domain expiry, and status pages in your Vantaj Uptime workspace.

Connect Google Analytics to ChatGPT. Query GA4 data in plain English and get instant insights.

Mezmo MCP is a remote Model Context Protocol (MCP) server that lets AI assistants and IDE chat agents interact with the Mezmo observability platform via the Model Context Protocol. Use it for streamlined observability, log analysis, and root-cause analysis in your favorite tools. Add Mezmo MCP and you can: 🕵️ Run advanced Root-cause analysis over recent logs 📦 List and describe Pipelines 📤 Export and filter Logs with powerful query syntax

Analyze web performance and get optimization insights from GTmetrix, directly in your AI workflow.

The statistical analyst in your AI chat — validated, citable, re-runnable analysis of your data.

Enables monitoring and management of Ruckus Unleashed WiFi controllers, including APs, clients, WLANs, and system events. MCP server for Ruckus Unleashed (tested on R500/R600, built-in Embedthis-Appweb web server). Uses aioruckus to talk to the controller's AJAX API.

Check infrastructure health, manage incidents, and run runbooks in Faultline.

Query metrics, targets, entities, and team data in your Steep workspace via MCP.

List datasets, schemas, run APL queries, and use prompts for exploration, anomalies, and monitoring.

Read-only MCP server for Yandex Metrika analytics. Query visits, sources, geography, devices and more in plain language — directly in Claude, Cursor, or any MCP client.

MCP-native AI SRE: ask what's broken in production, get a reviewed GitHub fix PR.

MCP-native AI SRE. 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 include list_problems, get_problem, query_traces, detect_anomalies, and request_problem_remediation. Human-in-the-loop by default — the merge button stays yours.

Interact with a global network measurement platform.Run network commands from any point in the world

Paid remote MCP for agent design system guard MCP, structured receipts, audit logs, and reviewer-rea

System self-awareness, health monitoring, and autonomous self-repair

Let AI agents monitor and manage your infrastructure through the Model Context Protocol. Query, create, and resolve — all in natural language.