"General search for the term 'Agent'" matching MCP servers:

Registers a set of inert, tempting decoy tools with any MCP-capable client so that any call from a hijacked or prompt-injected agent instantly raises an alert with full attack context and a per-call trace token. Also plants worthless canary tokens in honeypot files that trigger zero-false-positive leak alerts when they surface in agent output, files, or outbound requests.

MCP server for Google Search Console: properties, sitemaps, search analytics and URL inspection

Enables AI assistants to monitor and control Bambu Lab 3D printers over a local network via MQTT, including real-time status, AMS filament info, print control, and maintenance tracking. It supports guided setup, safety confirmations, read-only mode, and a built-in printer simulator.

A read-only MCP server for Google Search Console that lets you query search performance data, sitemaps, and URL index status from any MCP client.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

MCP server exposing AI agent observability tools: list, inspect, and deterministically replay recorded agent execution traces for debugging failures.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

MCP server for AI search crawler governance, brand safety, and search infrastructure auditing. Provides tools to audit robots.txt, canonical links, sitemaps, redirects, and send IndexNow notifications.

Brings live project context into Slack via MCP, enabling developer teams to check service health, recall team decisions, search code, and query project context directly from chat.

Enables an agent to list properties, pull clicks, impressions, CTR and position grouped by query, page, country, device or date, review and inspect sitemaps and URLs, and optionally submit or delete sitemaps via the Google Search Console API. It is stateless and credential-free, taking the Google access token from each request's bearer header so a single instance can serve many accounts behind an auth proxy such as Nango.

Exposes rate-limit and usage data for AI coding agent CLIs as MCP tools, enabling querying of usage snapshots and reset times.

Find the step that caused an AI agent’s failure. Ask your assistant why a run failed, see the evidence, and check whether a suggested fix works.

Enables AI agents to query Google Search Console and Bing Webmaster Tools data for verified properties, covering clicks, impressions, CTR and rankings by query or page, URL index inspection, sitemap listing and submission, and Bing crawl issues and traffic stats. It runs as a hosted remote MCP server, so nothing is installed locally.

Enables AI agents to self-report every tool call, token usage, decision, and session grade into a local SQLite store, so users can trace execution, audit reasoning, and see per-session costs in a local dashboard. Also supports proxy mode to intercept and trace MCP tool invocations for agents that cannot self-report.

An MCP server that provides append-only, tamper-evident local receipts for AI agent actions, capturing command executions, outputs, and handoff evidence.

A Model Context Protocol server that provides unified access to Google Analytics 4 and Google Search Console data through real-time analytics queries.

Enables AI agents to access Google Search Console search performance and index health data, including clicks, impressions, rankings, URL inspection, and sitemap management.

Shows your current Claude Desktop activity as Discord Rich Presence, including model, status, usage, and subscription info.

Local-first observability for AI agent stacks. Provides MCP tools for agents to check health, shadow configs, and burnout metrics proactively.

Enables read-only access to Google Search Console, Bing Webmaster Tools, and PageSpeed Insights, allowing queries for analytics, sites, sitemaps, inspections, crawl issues, and page speed analysis via natural language.

Enables MCP clients to work with webmaster search analytics, sitemaps, and URL inspection once the Google API integration is implemented, though the current scaffold does not yet call Google.

An MCP-powered AI platform for satellite mission control, enabling space weather analysis, orbital collision detection, satellite health monitoring, and secure command validation through natural language.

Enables AI apps to inspect and manage a NextDNS account in plain language — profiles, analytics, query logs, blocklists, security and parental control settings — with every change saved and reversible via undo. It runs self-hosted on your own computer or server, keeps per-profile read/write/hidden permissions, and requires double confirmation for deletions or overwrites.

Exposes network-monitoring tools (query metrics, analyze windows, compare, logs, status, runbooks, speed tests) as an MCP server for agentic workflows. Designed with evaluation suites, cost-aware model routing, and semantic tool retrieval.

Provides cost analysis of AI agent usage by previewing scrubbed metadata before upload and analyzing spend, cache-hit rates, and waste recovery through a local or remote server.

MCP server for AI agent observability, providing trace and span logging, search, latency/tokens/cost metrics, and anomaly detection using an in-memory buffer.

Enables AI agents to manage prompts and sessions via the ai-agent-logs API, with tools for health checks, login, listing/creating prompts, and retrieving sessions.

Connects AI assistants to a site owner's search performance data, letting them ask in plain language about clicks, queries, pages, indexing and sitemaps and get back structured results. Runs locally with your own credentials, read-only by default, and validates requests up front so the API's silent empty-result and terse-error quirks are caught before they mislead.

Tracks AI agent token usage and spending in real time, with budget alerts, per-task cost breakdown, and a visual dashboard.