Herramientas

Self-improving agent from Nous Research with built-in memory and a learning loop that turns experience into skills. Works with any model provider; the hermes command has a terminal UI, and a gateway connects it to Telegram, Slack and more and runs scheduled tasks.

Ultra-lightweight, self-hosted personal AI agent framework in Python: WebUI, terminal and chat channels (Telegram, Discord, Slack, WeChat, Feishu, email), long-term memory, cron, MCP and multi-agent delegation; reads PDF and Office files. OpenAI-compatible or local models; Python 3.11+.

Open-source personal AI assistant and agent harness, formerly chatgpt-on-wechat: plans tasks, runs tools and skills, self-evolving memory and knowledge, multi-agent teams. Channels: WeChat, WeCom, Feishu, DingTalk, QQ, Telegram, Slack; any major model provider. One-line install and web console.

Anthropic's official knowledge work plugin: manages tasks in TASKS.md, remembers colleagues, projects and internal jargon with two-tier memory, and generates a local dashboard. Can sync to-dos with calendar, email and chat tools.

Processes large tool outputs in a sandbox and returns only the results to context; logs session events in SQLite with FTS5 so work continues after context compaction. Supports Claude Code, Codex and a dozen other clients. ELv2 licensed.

Continuously records your screen and audio locally, extracting on-screen text and transcribing speech, so agents can search pages, docs and meetings you saw and summarize your day. Data stays local. Needs screenpipe running: source is free for personal use, desktop app is a subscription.

Turns an Obsidian vault into a local-first knowledge base: imports sources into interlinked notes with citations, answers questions from what is already in the vault, and adds 15 skills including search, vault health checks and Canvas knowledge graphs.

Learns your domain and working style over a few rounds of conversation, then generates a personalized Markdown knowledge system (folders, note templates, processing pipelines, hooks and maps) so agents remember knowledge across sessions. First setup takes about 20 minutes and is token-heavy.