"Accessing Your Supabase Projects Dashboard" matching MCP servers:

Enables LLM clients to interact with OpenSearch Dashboards, including reading saved objects, listing tenants and index patterns, and querying logs through the Dashboards API.

Enables AI assistants to monitor and manage Linux infrastructure including services, logs, processes, disk, memory, ports, cron, nginx, Docker, and system health checks via the Model Context Protocol.

Enables autonomous agents to convert raw telemetry, system metrics, and departmental status updates into executive decision briefs, KPI watchpoint summaries, strategic signal extraction, and automated mitigation recommendations.

Enables AI agents to query and monitor service status, latency, and performance through configurable checks (HTTP, TCP, SSL, keyword, JSON-path) and exposes tools for listing services, retrieving metrics, and running on-demand checks.

Read-only MCP server for querying AI usage metrics (exact tokens, cost, latency, errors, productivity) from a local SQLite database, enabling charts and analysis in Claude Code and Cursor.

Enables AI assistants to search Elasticsearch logs, retrieve log details, analyze service health, scan local codebases for APIs, and create Kibana dashboards.

Query OpenTelemetry logs, traces and metrics from a self-hosted OTLP dashboard.

A comprehensive Model Context Protocol (MCP) server for Grafana, Prometheus, Kafka UI, and Datadog. Features a secure "Bring Your Own Key" (BYOK) architecture where credentials stay local. Provides tools for metrics querying, dashboard inspection, Kafka lag monitoring, and unified health checks.

Maintenance, recovery, and observability for Claude Code. CLI + MCP server + dashboard.

Enables LLMs to query and analyze logs from SEQ structured logging server with capabilities for searching events, retrieving event details, analyzing log patterns, and accessing saved searches.

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

MCP-native health monitoring that probes MCP servers using the list_tools protocol handshake, detects version drift, stores history in SQLite, and generates an HTML dashboard.

Enables MCP-compatible agents to interact with Grafana instances for searching, creating, and updating dashboards, exploring logs via Loki, querying datasources, managing alerts, incidents, and on-call shifts, and accessing observability data.

Tracks and analyzes AI agent tool calls with event logging, dashboard, per-tool and per-agent analytics, and error monitoring.

Remote MCP server that normalizes OpenTelemetry GenAI spans by mapping fields, provider attributes, and missing attributes, and exports dashboard schemas.

Real-time analytics dashboard for Claude Code, tracking sessions, tool usage, file changes, and token costs via an MCP server.

Read and manage your Argulog error tracking data - issues, projects, alerts, releases, billing, and admin operations - from any LLM agent. Authenticates with a Personal Access Token from the dashboard: PAT scopes gate writes server-side.

ocal LLM proxy with semantic cache — Aho-Corasick normalization (1114 rules), metrics dashboard.

Password-protected dashboard and Remote MCP observer for Codex work, recording concise task milestones via observe_start, observe_report, and observe_finish tools.

Enables live tracing and observability of MCP tool calls, persisting execution traces to MongoDB and streaming them in real time to a dashboard.

An MCP server for accessing systemd journal logs.

Real-time observability dashboard for monitoring AI agents in multi-agent development workflows, with live WebSocket updates of tool calls, sessions, and usage statistics.

MCP server for Kibana / Elasticsearch — log search, aggregations, index discovery, and dashboard browsing. Hits Elasticsearch REST API directly for log queries; falls back to Kibana Console proxy when no direct ES URL is configured. Supports ApiKey auth (best for agents), Basic auth, and anonymous access. All 5 tools are read-only (readOnlyHint: true). Returns structured JSON (outputSchema).

The policy enforcement plane for MCP: deterministic admission and egress policy, attributable audit, and SIEM export for your MCP server fleet. Self-hosted and MIT licensed.

MCP-native agent evaluation and observability server. Log traces, evaluate output quality with 12 built-in rules (PII detection, prompt injection, cost thresholds), and track agent costs. Real-time dashboard, OTel-compatible spans. Self-hosted, MIT licensed.

Uptime monitoring from your AI agent: create and diagnose checks (40 types: HTTP, TCP, DNS, SSL, ICMP, databases, message queues and more), read results and incidents, and manage status pages and maintenance windows. Built into the self-hostable SolidPing server, served over streamable HTTP at /api/v1/mcp.

Laravel Telescope-style debugging for Hono apps whose dashboard endpoint is also an MCP server: read recent exceptions with the request that produced them, recent requests filtered by status or duration, one request in full, and the slowest queries. Five read-only tools, zero runtime dependencies.

Shows what is consuming your agent context window before a session starts: always-loaded skill descriptions ranked by token cost, skills installed more than once under different names, CLAUDE.md/AGENTS.md sizes including what their @import lines pull in, and MCP servers configured across clients. Read-only: no child processes, no network.

Every agent action is recorded in a SHA-256 hash chain. Prove to clients that your agent did what it said it did. Record, query, verify, and export agent activity.

Enables Claude to discover and understand infrastructure-as-code drift by listing projects with drift, analyzing Terraform plan outputs, and providing remediation information.

BeamScope gives AI coding agents access to your running BEAM application through a resilient TCP architecture that survives app restarts.

Enables MCP-compatible AI assistants to inspect projects, processes, ports, logs, HTTP endpoints, Git state, and development databases for local runtime diagnostics.

Lets an AI assistant answer performance questions from Tideways data by reading projects, metrics, issues and traces through the read-only REST API.

MCP server enabling AI assistants to interact with your LogicMonitor, providing 125 tools for comprehensive monitoring and management operations.

MCP-native LLM observability. Query your Spanlens traces, stats, cost anomalies, and savings from Cursor, Claude Desktop, or any MCP client. Open source (MIT).

Enables AI coding agents to see their Odoo.sh projects by listing projects, branches and builds, waiting for a build to finish, reading build and server logs, and optionally rebuilding branches or updating the firewall. It runs read-only by default with bounded, time-limited tool calls, keeping the user's Odoo.sh session out of the agent's reach.

Enables agents to interact with a GlitchTip instance for issues, events, projects, releases, alerts, uptime monitors, performance, and more via stdio or HTTP.

Give your AI ears and eyes and perception

MCP server that gives AI agents access to your application's OpenTelemetry traces for querying, analysis, and debugging.

MCP server — read-only log access for AI assistants. Debug your Linux server with AI, without giving the AI shell access.