Hodor vs ExploreRL

Capture Flutter traffic. Test APIs. Debug with AI. Hodor brings packet capture, API testing, and developer utilities to your iPhone and iPad. IP-layer capture can inspect traffic that does not follow system HTTP proxy settings, including traffic from Flutter apps. CAPTURE AND DEBUG • Capture and rewrite HTTP(S), WebSocket, TCP, and UDP traffic. • Inspect HTTPS requests and responses after configuring certificate trust. • Replace HTTP request and response data with Mapping, simulate responses with Mock, and replay requests without repeating actions in the original app. • Extend processing with JavaScript, filter by domain, export HAR, and forward HTTP traffic to other tools on your local network. • Preview Protobuf, Form-Data, JSON, HTML, JavaScript, and CSS. Start or stop the capture service with URL Scheme commands. MULTI-PROTOCOL API TESTING • Send HTTP(S), WebSocket, TCP, UDP, gRPC, and MQTT requests. • Organize requests into groups; manage environments, variables, authentication, headers, and bodies. Import and export cURL. • Combine pre- and post-request scripts, value extraction, and assertions for workflows such as signing in, reusing a token, and checking responses. AI TESTING THROUGH MCP Connect a compatible AI client to Hodor's MCP service. Give it a testing goal and let it inspect captured traffic, create and edit requests, send them, analyze responses, and adjust and retest in a multi-step workflow. MCP requires setup and an access token; Hodor does not include an AI model. Data read by the client may be sent to its configured model service. Script execution must be explicitly enabled. EVERYDAY DEVELOPER TOOLS URL, Base64, and Unicode encoding tools; URL parsing; JSON formatting; AES encryption and decryption; MD5 and SHA/HMAC hashing; JWT inspection; timestamp conversion; certificate hashes; regular expressions; and QR code generation—all in the app. Use Hodor only with traffic and systems you are authorized to test. HTTPS decryption depends on certificate configuration and app security policies. iOS background limits may interrupt MCP sessions. SUBSCRIPTIONS Some features require a paid plan. Monthly and yearly subscriptions are available; features, device coverage, and prices are shown on the purchase screen. Payment is charged to your Apple Account at confirmation. Subscriptions renew automatically unless canceled at least 24 hours before the period ends; renewal is charged within the final 24 hours. Manage or cancel in Settings > Apple Account > Subscriptions. Privacy Policy: https://ximlu.github.io/hodor/privacy_en.html Terms of Service: https://ximlu.github.io/hodor/terms_en.html

Train, visualize, and experiment with Reinforcement Learning algorithms entirely on-device with ExploreRL. Built with MLX, ExploreRL provides an interactive sandbox to test various environments and algorithms with different hyperparameters to observe how RL agents learn through trial and error. LEARN BY DOING Train agents on classic adapted environments and observe learning in real time. Watch values grow, track reward curves, and develop intuition for how different algorithms and hyperparameters affect performance. Read and learn about reinforcement learning concepts in the documentation. ALGORITHMS Four common implementations: - Q-Learning - SARSA - Deep Q-Network (DQN) for discrete action spaces - Soft Actor-Critic (SAC) for continuous control INCLUDED ENVIRONMENTS Adapted from classic standards: Toy Text: Frozen Lake, Blackjack, Taxi, Cliff Walking Classic Control: CartPole, Mountain Car, Mountain Car Continuous, Acrobot, Pendulum Box2D: Lunar Lander, Lunar Lander Continuous, Car Racing, Car Racing Discrete FEATURES - Environment-specific settings - Real-time training metrics and reward visualization - Configurable hyperparameters: learning rate, discount factor, epsilon decay, batch size - Agent library with save, load, duplicate, and export functionality - Evaluation mode to test trained agents without further training - Educational documentation covering RL concepts, neural networks, and algorithms - Custom seed for reproducibility Note: Training performance will vary by device. Devices with newer hardware and more memory will have a better experience.