"React Query" matching MCP servers:

Bridges React Native DevTools, enabling AI assistants to debug, profile, and inspect React Native applications through a standardized protocol.

Enables AI agents to read and optionally write to PostgreSQL databases through a multi-project setup with schema inspection, query execution, and performance analysis tools.

Enables read-only querying of Azure Log Analytics and Azure Resource Graph through MCP, supporting KQL queries, workspace discovery, and resource inventory exploration with Azure RBAC authentication.

MCP server for querying and analyzing TensorBoard event files, enabling AI agents to extract scalar data, statistics, and correlations without a running TensorBoard server.

An MCP server that connects to your React Native application debugger

Provides AI agents with visibility into React applications by exposing tools to inspect component state, props, and performance metrics. It enables debugging and state analysis for both web and React Native applications through the Model Context Protocol.

Enables users to ask about render performance in React and React Native apps via natural language, exposing tools for listing render hotspots and explaining component re-renders.

Enables AI assistants to inspect React Native app performance including memory, rendering, frames, and network requests, providing plain-language summaries and shareable reports.

Connects AI agents to a running React Native app so they can see the screen, tap and type, and inspect logs, network traffic, and state without any SDK or code changes. Composite tools let an agent run a whole interaction flow in a single call instead of one round trip per tap.

Exposes a metrics query API to AI assistants, allowing them to issue queries and interact with the server's tools such as ping.

Streams live React profiler data to AI agents, enabling them to analyze performance and suggest specific, actionable fixes for slow components.

Monitors host CPU/RAM, local ports, and Docker containers, streaming live telemetry to a React dashboard over SSE. Exposes MCP tools to query system status, read environment logs, and execute remediation fixes via a local LLM agent.

Logs LLM interactions to local CSV or Markdown files with automatic categorization for detailed tracking. It provides an interactive HTML dashboard to visualize query volume, model usage, and category distribution.

Enables querying logs and metrics with plain SQL from any MCP client via pooml's read-only query API.

Minimal MCP server that integrates with Graylog, enabling agents to search, analyze, and inspect log messages across streams, discover fields and streams, and query multiple Graylog instances.

MCP server that transforms raw log query results into structured incident reports (Markdown, JSON, HTML) with correlation to git commits and tickets.

Honeypot threat intelligence for AI agents. Query 90 days of probe data from our sensor network: IP reputation, scanner classification, CVE probing trends, TLS/SSH/JA4 fingerprints. Free tier 500 credits/day, OAuth + bearer auth, streamable HTTP at https://mcp.honeylabs.net/mcp.

MCP server for Prometheus metrics and observability. Give Claude (or any MCP-capable agent) read access to your Prometheus instance — query metrics with PromQL, inspect active alerts, and explore scrape targets without leaving the conversation. Tools: prometheus_list_metrics, prometheus_query, prometheus_query_range, prometheus_list_alerts, prometheus_list_targets.

Postgres performance MCP server that analyzes hotspots, explains query plans, and detects dead-weight indexes. It aims to produce evidence-backed recommendations through a verification loop.

MCP server for analyzing Perfetto traces with LLMs — query .pftrace files in PerfettoSQL via Claude Code or any MCP client