"Deep research on Gemini" matching MCP servers:

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

Provides read-only on-demand ServiceNow reports for system logs (syslog) and developer work (update set changes), with automatic pagination and date filtering.

Connect AI agents like Claude, Cursor, and Gemini to historical Windows performance and privacy data gathered by the AppControl Windows app. This server enables natural language queries into CPU, GPU, and temperature history alongside system security events for deep local auditing.

Enables generating on-chain attestations of agent service performance across Ethereum, Polygon, Arbitrum, Optimism, and Base, plus audit trail retrieval, attestation verification, and price lock lookup.

Enables Google Gemini and any MCP-compatible client to securely monitor and manage hypervisor guests — starting, stopping, rebooting, snapshotting, rolling back, and backing up VMs and containers — through the Model Context Protocol over Streamable HTTP with OAuth 2.0/OIDC authentication.

Provides structured MCP tools for local runtime observability and debugging of React Native/Expo apps on Android, enabling evidence-first diagnostics such as screenshots, UI trees, per-request network capture, performance metrics, and CDP-based console/heap/profiling exports.

A trademark research and monitoring MCP server that provides access to a normalized trademark corpus across 30+ registers, with provenance on every record, watch/monitoring capabilities, conflict research via Nice class, and portfolio management tools—without returning legal verdicts, leaving availability judgments to qualified professionals.

Enables agents to inspect React Native and Expo apps through React's runtime tree, identify source locations, act on elements without coordinates, and verify outcomes with assertions and runtime evidence.

MCP server for system monitoring, enabling users to ask about CPU, memory, disk, network, and processes on their system.

Bridges Microsoft Clarity's analytics API with Claude, enabling custom date ranges and page-level filtering on top of Clarity's native limitations.

MCP server exposing rlg (RustLogs) log files as tools for on-call / SRE agent workflows. Three tools over JSON-RPC stdio — tail_log (last N events, filtered by level/target), filter_log (predicate filtering), summarize_errors (grouped error taxonomy). Pure Rust. MIT OR Apache-2.0.

Measures what MCP servers cost in context tokens: probes a URL or a local command now, measures a whole config file, and looks up the daily results for every server in the official MCP registry on mcpcost.ulehla.dev.

Enables log analysis for Tenable Patch Management (SaaS and on-prem) by parsing, de-duplicating, and decoding server/client logs into structured verdicts, ranked issues, and known-issue fixes.

It enables solo builders to automatically log product changes to PostHog and later get statistically honest verdicts on whether those changes moved key metrics, without needing enough traffic for A/B tests.

Tamper-evident audit logging for AI decisions. Three tools (record_decision, verify_decision, list_decisions) write to a regulator-grade ledger built on AWS S3 Object Lock with 7-year retention. Designed for EU AI Act Article 12 and FCA SS1/23 evidence requirements. Try zero-config: npx audit-ledger-mcp boots in sandbox mode against a public hosted tenant.

Read-only MCP server exposing AGmind Systems Lab's measured local-LLM benchmark claims (TTFT, inter-token latency, task success, etc.) on AMD Strix Halo and DGX Spark hardware via search, claim lookup, and measured-combination listing tools.

DBeast MCP is a robust, security-first Model Context Protocol server designed to empower AI coding assistants (like Claude Desktop) with deep PostgreSQL database insights. Instead of just running basic SQL queries, DBeast equips your AI agent with tools to inspect active locks, audit slow queries, analyze table schemas, and safely generate index recommendations in real-time. Built specifically for

A lightweight npm MCP server for deep Redis diagnostics, offering tools for memory, slowlog, clients, keyspace, latency, and config analysis with AI-powered recommendations.

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.

Uptime monitoring your AI agent can set up: create HTTP, SSL, ping, TCP and DNS monitors checked from multiple regions, run checks on demand, read and acknowledge incidents, manage cron heartbeats, maintenance windows and status page updates.

Enables interaction with Jira Service Management Operations alerts and on-call schedules, including searching alerts, reading notes and activity logs, acknowledging, closing, annotating, adding responders, and querying current and next on-call rotations.

Exposes live industrial IoT telemetry to any MCP client, streaming simulated sensor data from a fleet of machines and detecting anomalies, with the ability to inject faults on demand.

Enables MCP clients to run fresh audits of any public web page on mobile or desktop, returning category scores, lab metrics, and prioritized findings for performance, accessibility, best practices, and SEO. Each call performs a new uncached audit, so users can compare results within a conversation.

Pull open jobs from Workday, Greenhouse, Lever and Ashby career sites as normalized JSON with one tool call. Change tracking returns only jobs added, edited or closed since the previous run. Calls the hosted Apify Actor: set APIFY_TOKEN; tool calls are billed pay-per-event on Apify. No browser, login or proxy.

Enables agents to query GPU availability across SSH hosts, find free GPUs, list hosts, and inspect fleet status using only nvidia-smi on the remote side.

Verifies AI outputs in real-time across 6 dimensions, with automatic retry and failover to ensure correct, complete, and reliable LLM responses before they reach the user's editor.

Read-only AMD GPU monitoring for Claude on Linux — VRAM, temperature, clocks, power, and running ML processes via rocm-smi.

Enables SEO audits and URL monitoring via the SEO Radar API from any MCP-compatible AI client.

Enables AI assistants to query self-hosted OxiLytics analytics for app downloads, crashes, reviews, and sync health, with a read-only design that keeps data on your own server.

Provides twelve read-only tools that report how often ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews name and cite a brand, covering visibility, share of voice, sentiment, competitor mentions, sources, alerts and ranked recommendations with the underlying answers. It lets users query these measurements directly from Claude, Cursor or any MCP client, with denominators and null-handling rules included so results are interpreted correctly.