"Creating a Document as a Knowledge Base" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Fixter's MCP provides a stream-lined agentic way to onboard, setup and use the Fixter monitoring and observability platform. Check out more at https://fixter.dev/
Website traffic, human vs bot split, realtime visitors, breakdowns and site health for your DevDome sites. Hosted remote MCP server (streamable HTTP), authenticated with a DevDome API key.
Private work routing for authorized buyers and agents, with Zinvyl as the first enabled supplier.
Ask an agent why a PHP site is slow: every request with its SQL, HTTP calls, errors and N+1.
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.
Watchdog for unattended AI agents: alerts, evidence checks and a verifiable proof per run.
Search + patterns, maturity assessment, context pricing, redaction checks - a practice as tools.
Public read-only demo of Netmon's network monitoring tools over a recorded snapshot.
AI/LLM agent output audit MCP: policy eval, tamper-evident chain, AI safety, x402 USDC on Base.
Dead-man's-switch for cron jobs & AI agents. Import a crontab to arm one silent-miss alert per job.
A managed runtime for custom API integrations. Manage lines, endpoints, keys, logs and DLQ via MCP.
Free MCP window into a live autonomous machine-economy experiment: telemetry, hypothesis scoreboard.
MCP-native AI SRE: ask what's broken in production, get a reviewed GitHub fix PR.
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.
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
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Governance and grounding layer for engineering teams running AI coding agents (Claude Code, Cursor, Codex). Grounds agents in your codebase's knowledge graph, and adds session audit, policy controls and cost/token visibility.
Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.
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.
Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith
Dead-man switch for cron and webhooks: ingest URL, miss detection, alerts and a status feed.
