"Information about SQLite: a lightweight database engine" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Ask your AI about your EventSend events, delivery health and usage.
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.
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.
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.
Dead-man switch for cron and webhooks: ingest URL, miss detection, alerts and a status feed.
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.
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.
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.
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.
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.
