"React Query" matching MCP servers:

An MCP server that runs parallel AI agents to analyze React components for performance issues, including unnecessary re-renders, memoization errors, bundle size problems, and profiling concerns.

An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.

Turnkey on-premise private Agentic AI on NVIDIA DGX. Query specs, model CapEx ROI & join Partner Program.

Enables MCP clients like Claude Desktop to query DEXUN AdWhiz for ad account lists, AI recommendations, savings summaries, recent activity, and API quota, all read-only.

Enables AI agents to call LLM APIs via x402 micropayments in USDC on Base network, manage a local wallet, and query consumption records.

Advanced MCP server that uses OpenRouter and Perplexity APIs for enhanced query processing with multi-vendor support, query type optimization, file attachments, and robust retry logic.

Model Context Protocol server for AI Canvas. Search, inspect, and install open-source React and Tailwind components from the aicanvas.me registry directly in your AI editor.

An MCP server that translates natural-language queries into structured catalog searches using Amazon Bedrock, enabling MCP clients to query existing in-house APIs.

Global price benchmarking for AI inference across 2,600+ SKUs from 47 vendors. Query live pricing, market indexes, and model specs via 8 tools. Free tier available.

Enables coding agents to query AI model API prices, including historical point-in-time lookups with cited sources, using a bundled dated dataset and requiring no API keys.

Enables AI assistants to query KumoRFM for predictive analytics on relational data, including graph management, natural language to PQL conversion, and training-free predictions.

Enables AI coding assistants and agent workflows to query live measured free-LLM performance and availability, including throughput, uptime, tool-calling success, and model diagnostics.

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

Manages a local fleet of llama.cpp GGUF models, enabling AI agents to discover, start, stop, test, and query evaluation results for llama-server processes.

Enables AI agents to query LLM and multimodal model benchmarks, pricing, speed, and track model updates via structured diffs using the Artificial Analysis public API.

Lets AI agents query, manage, and operate their LLM observability data directly from the conversation. Provides 87 tools for cost analysis, alerting, anomaly detection, and runtime control gates.

Enables agents to query the TypeSafe Jev decision model for typed answers—yes/no, choice, and score questions—with calibrated probabilities, batched in a single request under a local context-budget guard.

Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.

Enables AI assistants to query Google AI (Gemini models) via Vertex AI or Google AI Studio with automatic tool selection, multi-turn reasoning, and multimodal input support.

Lets Claude query and manage a local Ollama server — list models, inspect them, run generate/chat completions, pull or delete models.