"Improving React Native Development Experience" matching MCP servers:

Enables AI agents such as Cursor and Claude Desktop to read a running debugger's captured console logs and network sessions, inspect full request/response payloads, diagnose crashes and failed API calls, and trigger React Native reloads or the developer menu.

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

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

MCP servers for real-time development monitoring and interactive pair programming.

A DataOps-focused Kafka MCP server with consumer lag diagnosis and broker health monitoring, featuring incident-based diagnosis logic derived from real CDC pipeline operational experience.

MCP server for measuring, tracking, scoring, and improving AI agent reliability with tools for recording interactions, scoring reliability, analyzing failures, recommending improvements, generating audit reports, and checking MCP health.

AI-native developer observability MCP (Model Context Protocol) server that gives AI agents full-stack visibility into your development environment — browser, terminal, and processes — all in one unified interface.

Allows AI assistants to query Tingyun (Wukong) platform monitoring data for App, Browser, and MiniProgram, covering performance, exceptions, user experience, network, and more via RUM REST API.

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.

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.

An AI-powered server that analyzes system log files to identify errors/warnings and recommend fixes using FastMCP, LangGraph ReAct agents, and Anthropic Claude.

Enables autonomous context window management, prompt caching, token optimization, and real-time observability for AI coding agents across multiple IDEs, reducing token costs and improving performance.

Exposes the React Native performance harness to any agent, letting it connect to a running dev build, capture render and flamegraph traces, and turn them into deterministic findings with ranked per-route tables. Enables agents to run A/A noise-floor calibration, interleaved A/B measurements, gates, and PR-body generation from validated verdicts.

Reliability intelligence for remote MCP servers. Agent-native discovery for 1,700+ servers with uptime monitoring and latency benchmarks.

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.

Enables MCP-compatible AI assistants to inspect projects, processes, ports, logs, HTTP endpoints, Git state, and development databases for local runtime 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).

DCL Trust Oracle is a deterministic AI audit layer, natively integrated with MCP, that evaluates LLM and agent outputs against configurable policies before and after action. Every verdict is written to a tamper-evident, hash-chained audit log storing only cryptographic metadata — never raw content — enabling privacy-first forensic review.

Provides transactional intelligence for AI agents, enabling safe tool execution with pre-flight invariant checks, sub-second filesystem snapshots/rollback, causal tracing, belief contradiction detection, and 15 native MCP tools for Claude Code.

Enables LLMs to analyze and manage DBOS workflows, including introspection, workflow management, and authentication, to help debug applications in development or production.

Enables AI agents to run container forensics, generate container obituaries, and audit git repository history as native MCP tools, producing markdown reports they can reason over.

Provides AI coding agents with real-time visibility into local development runtime state, enabling them to tail application logs, inspect ports, monitor process metrics, and diagnose network errors.

A secure, local-first MCP server for read-only inspection and troubleshooting of development environments, exposing narrow, typed, auditable capabilities for repository inspection, log summarization, Docker review, and security scanning without granting unrestricted machine access.

Enables querying OpenTelemetry logs stored in OpenSearch across development and production environments. Provides tools for searching logs by various criteria including free-text Lucene queries, trace IDs, service names, error levels, and specific fields.

A local-first MCP bridge and script operations layer that connects coding agents to authorized Roblox Luau development clients via websocket, enabling live execution, file watching, diagnostics, permission-gated script capsules, crash detection, and a dashboard.

Provides an MCP-native operational interface for diagnostics, explainability, regression checks, and operational memory on data-system internals like PostgreSQL and Databricks toy engines.

Zyvor Atlas is an Apache-2.0 storage control plane over Ceph, NFS, ZFS, Longhorn and a native filesystem. Its self-hosted MCP server (streamable HTTP, bearer-JWT auth, tenant-scoped) gives agents 27 read-only tools: inventory, Ops Advisor risk scoring and incidents, anomaly detection, what-if capacity planning, eBPF-backed I/O risk, Ceph status and OSD tree, disaster-recovery status, DataBridge mi

A remote MCP server that enables real-time interaction with the Dynatrace observability platform, bringing production-level monitoring data directly into development workflows.

MCP-native health monitoring that probes MCP servers using the list_tools protocol handshake, detects version drift, stores history in SQLite, and generates an HTML dashboard.

Monitors development server logs in real-time and provides Claude with immediate error notifications via Server-Sent Events. Intelligently parses TypeScript, Svelte, and Vite errors with severity classification and file correlation.