ottomator-agents - AI Agent Applications Tool

Overview

ottomator-agents is an open-source collection of AI agent implementations and workflow JSON used by the oTTomator Live Agent Studio. The repository collects dozens of ready-made agents (for example: advanced-web-researcher, multi-page-scraper, RAG templates, n8n workflow agents and sample Python agents) so developers can inspect, run, or adapt concrete agent patterns and integration examples. ([github.com](https://github.com/coleam00/ottomator-agents)) The project is positioned as an educational and practical sandbox: agents demonstrate real patterns (RAG, multi-tool orchestration, web research, content generation, n8n integrations) and many agents include Dockerfiles or containerized templates to simplify deployment. The Live Agent Studio also offers hosted execution of agents (tokenized usage for hosted runs), while the GitHub repository provides the full source and deployment examples for running locally or customizing for production. ([github.com](https://github.com/coleam00/ottomator-agents))

GitHub Statistics

• Stars: 5,296
• Forks: 1,868
• Contributors: 3
• License: MIT
• Primary Language: Python
• Last Updated: 2025-11-09T21:46:45Z

The repository shows strong community interest and active maintenance: the GitHub project lists ~5.3k stars, ~1.9k forks and 3 contributors, and the repository is organized with many agent subfolders and frequent commits. These signals point to an active, learning-focused project with many example implementations to study. ([github.com](https://github.com/coleam00/ottomator-agents)) Activity and community signals to watch: there are open issues and pull requests (users filing runtime and README improvement issues), and the repo currently does not include a SECURITY.md. Contributors and users discuss and share agents in the oTTomator Think Tank community and hackathons tied to the Live Agent Studio. These give an indication of a lively ecosystem but also suggest you should review open issues before deploying agent code. ([github.com](https://github.com/coleam00/ottomator-agents/issues?utm_source=openai))

Installation

Install via docker:

git clone https://github.com/coleam00/ottomator-agents.git

cd ottomator-agents

cd <agent-folder>  # (choose the agent you want to run, e.g. advanced-web-researcher)

docker build -t <agent-name> .  # many agents include a Dockerfile or use a shared base image

docker run --env-file .env -p 8080:8080 <agent-name>  # supply required env variables per-agent README

Key Features

• Large catalog of agent examples (RAG, research, scrapers, content creators).
• Several n8n workflow agents demonstrating no-code/low-code automation patterns.
• Dockerized agent templates and a shared base Python image for consistent builds.
• Sample Python and Voiceflow agent templates for quick local testing.
• RAG strategies and knowledge-graph agent examples for retrieval workflows.
• Hosted execution via Live Agent Studio (token-based runs for hosted LLM costs).
• Agent developer guide and sample workflows to help contributors onboard quickly.

Community

Active and growing: the repo has thousands of stars and forks and a small core of contributors, with frequent mentions on community feeds and inclusion in oTTomator hackathon/discussion threads. Users file issues (runtime errors, dependency questions) and request README improvements; the project is healthy for learning and experimentation but reviewers should test agent code and watch open issues. The Live Agent Studio provides a separate community (Think Tank) for discussion and showcases. ([github.com](https://github.com/coleam00/ottomator-agents))

Key Information

• Category: Agent Applications
• Type: AI Agent Applications Tool