Provides a native desktop interface to install, configure, and chat with Hermes Agent—handling local or remote backends, provider setup, sessions, memory, and tools. Ships a guided installer, streaming SSE chat UI with token tracking, persona/profile management, messaging gateways, and cron scheduling.
Provides a cloud-backed shared memory and skill-propagation layer for coding agents: captures session traces, mines recurring patterns into reusable SKILL.md, and shares capabilities across agents in real time. Features hybrid semantic+lexical search, BYOC storage, and a VFS for traces — built for team workflows and agent orchestration.
Compresses LLM/agent replies into a terse “caveman” style to cut output tokens (~65–75%) while preserving technical accuracy. Offers per-agent skills, intensity modes, memory-compression and middleware to lower token cost and extend usable context.
Automates scanning and evaluating job listings with LLM-driven agents, then generates ATS-optimized, per-role PDFs and a unified tracker. Supports batch processing and terminal-first workflows with structured A–F scoring and portal scanners.
Provides fully local long-term and symbolic short-term memory for AI agents via a 4-tier layered pipeline and Mermaid canvases, with zero external API dependencies. Key features: lossless drill-down from personas to raw traces, hybrid retrieval, and ready integrations for OpenClaw and Hermes.
A local-first web and desktop dashboard for Hermes Agent that runs multi-agent LLM chats, manages profiles/providers/models, schedules automated jobs, and connects platform channels (Telegram/Discord/Slack/etc.) with built-in TTS, file browser, and usage analytics.
A local-first web and desktop dashboard for Hermes Agent that runs streamed agent chats, manages profiles/providers/models/credentials, schedules cron jobs, and inspects files and terminals across local, Docker, SSH and Singularity backends.
Provides a local-first web-intelligence layer for AI agents: search, fetch, crawl, extract, cache, find-similar and agent-style research without API keys or per-query billing, running as an MCP server, REST daemon, or SDK.
Turns plain-English system or process descriptions into polished, themeable architecture, workflow, sequence, data-flow and lifecycle diagrams as a self-contained HTML file, with one-click theme toggle, copy-to-clipboard and export to PNG/JPEG/WebP/SVG (native up-to-4× rasterization).
Runs multiple AI agents in parallel inside a single macOS browser, giving each agent an isolated Space that can use your real logins without touching your tabs; controllable via an ego-browser JavaScript skill to perform web automation with fewer tokens and faster task completion.
Terminal-native AI coding assistant optimized for the deepseek-v4 model. Provides configurable "thinking" modes and reasoning-intensity controls, agent skills for extensibility, MCP integration, and a shared config with a VSCode plugin.