"Multi MCP (Model Context Protocol) implementation or management" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
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.
Read a tool-call log from an AI agent run and see which calls failed, looped or were slow.
Cost per run, tool, model and day for AI agents, from one call or an OpenTelemetry export.
Read Airbrake projects, error groups, notices, deploys and stats; mute or unmute error groups.
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
Observed facts on public MCP servers: protocol checks, tool changes, signed evidence. No verdicts.
Search + patterns, maturity assessment, context pricing, redaction checks - a practice as tools.
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?
A managed runtime for custom API integrations. Manage lines, endpoints, keys, logs and DLQ via MCP.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
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.
DriftOracle - 15 tools for model/data drift monitoring: PSI, KS-test, alerts, evidence packs.
Read-only server insight: why a Linux server or K8s cluster is slow, failing or changed.
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
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.
