Create Agents Autonomously with Voice or Natural Language

Speak or type a description like "build a deep research agent on large language models running daily at 9:00 a.m." and Toolhouse auto-configures the full pipeline using its tools for scraping, summarizing, and outputting sources. A 10-year-old could build sophisticated agents in minutes, as shown in demos automating Google services: scrape news topics, input to Docs, summarize, email results. Test immediately in the workbench chat—query it directly (e.g., "today's deep research on LLMs") to get outputs like Claude Mythos updates with sources. Edit outputs by instructing changes, share via chatbot link, or schedule runs. This eliminates backend setup, letting non-coders orchestrate multi-tool workflows instantly.

Add RAG, Files, and Integrations for Enhanced Capabilities

Upload docs/PDFs for instant RAG knowledge—agents reason over private files (e.g., summarize a PDF on a YouTube AI channel). Enhance with 100+ integrations: connect Gmail to auto-email daily briefs (e.g., LLM intelligence with Anthropic's Mythos, Spud sources). Search/add functions like "send email" in agent edits, update system prompt ("send briefing to myemail@domain.com"), save. Templates speed starts (e.g., invoice processing). Manage OAuth connections/logs centrally to revoke access or debug. Result: agents handle research, summarization, emailing end-to-end, saving hours on repetitive tasks.

CLI and API for Developers, Embed Anywhere

Install Toolhouse CLI (th login, th new doc-agent), add files/tools, deploy (th deploy), test via browser (th open) or API. Embed in apps: copy agent prompt, paste into Lovable to auto-build a chat UI powered by your Toolhouse agent—query for LLM research summaries with sources. Use MCP server hookups with Zapier/Pipedream/Smithery for coding agents to configure via CLI. Access via API endpoints for production integration. Trade-off: CLI suits devs for custom RAG/code-running agents but requires commands vs. no-code voice speed.