"Understanding the term 'throw' in web contexts" matching MCP servers:

Enables Claude Desktop to access the hosted Web Speed API through MCP, requiring only an API key for setup.

Give your AI ears and eyes and perception

A verifying MCP gateway that pins approved tool manifests and skill files to content addresses, blocking tampered descriptions before they reach model context.

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

Enables natural language interaction with Plausible Analytics data to query traffic, visitors, engagement, and more using conversational questions.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

Enables an AI agent to perform read-only inspection of Palo Alto Networks Panorama and PAN-OS firewalls for monitoring and troubleshooting, including inventory, health, network, logs, and policy queries. It communicates via the PAN-OS XML API over HTTPS and does not allow configuration changes.

Read-only MCP server that surfaces UniFi network data from a UCG-Fiber console to Claude, enabling monitoring of hosts, sites, devices, clients, ISP metrics, and device stats via read-only API tools.

Self-hosted web analytics platform that exposes analytics data via the Model Context Protocol, enabling natural language queries about traffic, page views, web vitals, and custom events.

Enables log analysis through MCP tools for searching logs, retrieving error contexts, and summarizing incidents with self-verified root-cause hypotheses.

Enables advanced management of Kubernetes clusters through natural language interactions. Supports querying, managing, and monitoring pods, deployments, nodes, and logs across multiple contexts and namespaces.

A persistent activity log server that allows MCP-compatible AI assistants to log events, decisions, and system logs over HTTP, with a built-in web dashboard for monitoring and searching logs.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

Provides cryptographically signed, tamper-evident compute usage receipts via a Model Context Protocol server, exposing tools to record usage, verify receipts, list the ledger, and verify ledger integrity without requiring any account, API key, or single cloud provider.

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.

Web analytics and AI session replay for agents: visitors, breakdowns, funnels, goals, revenue attribution, and AI-found site issues. Connects to the hosted Flowsery MCP server.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

16-tool MCP server for Google PageSpeed Insights & Chrome UX Report APIs. Analyze, compare, and optimize web performance directly through Claude, Cursor, or any MCP-compatible AI client.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

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.