"How to Find and Fix Bugs in a React Native App" matching MCP servers:

Provides comprehensive tools for React Native development, automating project initialization, version management, upgrades, Expo integration, and development workflows through AI assistance.

Enables macOS computer-use automation through public Apple APIs, supporting app and window discovery, clicking, typing, scrolling, and field setting via accessibility controls.

Enables orchestrator agents to route coding tasks to native CLI worker agents via MCP, providing tools for agent discovery, task submission, waiting, inspection, and cancellation.

An MCP server that lets Claude Code delegate durable background tasks, reasoning profiles, thread resumption, and native image generation to your local Codex CLI.

Enables validation of FIX messages against onboarding rules and automates onboarding workflows through MCP tools, using a LangGraph agent with LLM-based parsing and error explanation.

Enables AI agents to profile React applications, detect performance bottlenecks, and automatically apply fixes like memoization and code hoisting.

An MCP server that translates human GUI actions into machine-executable commands, enabling AI agents to control real software applications like Zoom, Excel, and WeChat via natural language or API calls.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

MCP server for the Neuralpunk.app Phase 1 slice, enabling AI agents to read approved capabilities, join resident debates, and propose Signals while preserving canon integrity.

Enables AI sales agents to interact with a CRM via event-sourced actions, identity resolution, guard checks, and an approval inbox, managing communications and tasks while adhering to compliance rules.

Enables AI agents to connect to Revit 2024 via MCP, inspect documents and selections, query and modify elements, and validate, preview, or commit plans with audit logging and rollback.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

An orchestrator MCP server that takes a plain-language app description and guides agents through a full workflow from intake to deployment, including design, audit, and maintenance.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Allows agents to get the current location of the user based on their IP Address or to fetch the location of any IP Address.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

A server that enables AI assistants to interact with Linear's project management tools through the Model Context Protocol, supporting features like searching, creating, and updating issues, adding comments, and retrieving user profiles and team information.

A Model Context Protocol server that converts Markdown content to HTML format.