"An overview or information about file systems" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Read your team's hosted journal from an AI agent: every machine's streams, in hub order.
Send and receive webhooks without building delivery queues or customer webhook controls. Relin lets your software and AI assistants set up inbound handlers, manage outbound events and customer endpoints, inspect delivery health, and retry failed deliveries. A generous free plan is available; no paid subscription is required.
Ask your AI about your EventSend events, delivery health and usage.
Is GitHub, npm, Cloudflare or your AI provider down right now? 20 status pages, one call.
Free-trial AI fleet spend meter. Quote agent fleet spend from token usage. 100 calls or 14 days. No auth. Official MCP Registry: io.github.mtardy90-sudo/bootlace-ai-spendmap.
Oviond brings data from 100+ marketing platforms into one reporting platform. Through the Oviond MCP server, AI assistants can securely access and work with Oviond clients, projects, reports, dashboards, widgets, and marketing data. Ask questions about your reporting data, analyze marketing performance, and manage reporting workflows directly through your AI assistant.
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
Health and token cost of every remote MCP registry server, probed daily. Look up, search, or probe.
Ask an agent why a PHP site is slow: every request with its SQL, HTTP calls, errors and N+1.
Free spend report from an agent log, no key. Hosted proxies: caps, audit export, buy calls.
Read-only MCP for AI usage profiles, leaderboards, stats, and docs; no writes or private data.
Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?
Live health and AI-readable metadata of invokera.com. Demo of an Invokera-hosted MCP server.
Public MCP digital twin with synthetic systems and an agent firewall. No customer data.
An inter-agent graffiti wall for one completely optional trace.
The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.
The Cortex MCP server provides read-only access to real-time engineering context from the Cortex developer portal, allowing AI coding assistants to answer natural language questions about your organization's catalog (microservices, libraries, domains, teams, infrastructure), scorecards (engineering standards and best practices), initiatives (goals and deadlines), and Engineering Intelligence metrics. It includes tools for querying documentation, tracking personal entities, and accessing AI-assisted insights across the entire Cortex ecosystem.
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.
Analytics for MCP servers. Find out which of your tools agents get wrong. MCPulse shows you which tools AI agents retry, which come back empty, and which they never call at all. Two lines inside your own server. It never sees your arguments or your results. getmcpulse.com
Investigate security events and manage the allow/deny lists an analyst acts on.
