"Information about Query Futures or Future Contracts" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Ask your AI about your EventSend events, delivery health and usage.
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.
Is GitHub, npm, Cloudflare or your AI provider down right now? 20 status pages, one call.
Uptime and website monitoring for AI agents. Query monitor status, incidents, heartbeats, domain expiry, and status pages in your Vantaj Uptime workspace.
Read-only MCP for AI usage profiles, leaderboards, stats, and docs; no writes or private data.
Read AFMR failure modes and discover scoped attestation and lift-evidence contracts.
Query analyzed WebRTC sessions: observations, deductions, experience scores, and AI summaries.
Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?
GraphQL operation count, query discarded
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
Query Checkly synthetic monitoring — checks, statuses, results, alerts, reporting and dashboards.
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.
Analytics for MCP servers. Query your tool calls, first-call success, retries and schema cost.
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
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
- Session Replay MCPOAuth unavailablecom.session-replay
MCP for retrieving information about recorded session replays.
Connect engineering metrics, DORA performance, and deploy risk scoring to any AI assistant. Score PRs for deployment risk using a 36-signal model, query team health, incidents, coverage, and more.
Real-time web analytics for AI agents: query traffic, funnels, revenue, and manage your sites.
