agentmake is an open-source agent development kit (ADK) for building agentic AI applications. Below are 15 autonomous agents & workflows apps with similar functionality to agentmake, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
agent-genesis is an open-source SDK and CLI/API toolkit for evaluating and testing AI agents. It provides developers with tools to benchmark, analyze, and improve agent performance during the development lifecycle.
Multi-agent orchestrator for AI coding tools
agent-template-pack is a curated collection of production-ready templates for building multi-agent AI systems. It helps developers quickly scaffold and deploy agent-based architectures, supporting rapid prototyping and robust deployments. Distributed as an open source package.
agentdef is an open-source CLI tool and specification for defining AI agents in a portable, framework-agnostic way. It enables developers to standardize agent definitions and streamline deployment across different AI frameworks.
agent-squad is an open-source Python framework for creating, orchestrating, and managing squads of autonomous AI agents. It provides a CLI interface and is designed for developers and researchers building complex agent-based systems. The project is licensed under Apache 2.0 and available on GitHub.
agent-kernel provides a method for creating stateful AI agents using only three markdown files and a git repository. It enables agents to retain memory between sessions, take notes, and build on previous work without requiring a separate framework or database. md files as project instructions, such as OpenCode, Claude Code, Codex, and Cursor, among others. md indexes knowledge files. Additional directories include knowledge/, which holds mutable facts about the current state of the world, and notes/, which contains append-only daily session logs. This structure allows agents to update facts as reality changes and maintain a narrative of decisions and actions taken during each session. Each agent operates in its own repository, making it possible to manage multiple agents with distinct identities and knowledge bases using the same kernel. To use agent-kernel, users clone the repository, start their coding agent within the cloned directory, and interact with the agent, which will prompt for its identity and remember information provided. The tool does not require a database or additional infrastructure, as all state and memory are managed through the markdown files and git. For those seeking additional features such as integration with Telegram, Slack, and daemon mode, a separate runtime called kern-ai is available and built specifically for agent-kernel, supporting multiple channels and user management. agent-kernel is positioned as a tool for developers or users who wish to create and manage AI agents with persistent memory using a lightweight, file-based approach.
agent-mini is an open-source CLI tool that acts as a lightweight personal AI agent, automating shell, file, and web tasks. It supports both local and cloud LLMs, making it ideal for developers and power users seeking AI-driven automation from the command line.
agent-company-ai is an open-source Python package that enables users to create and manage a business operated by AI agents. It provides automation tools for business processes, allowing developers and AI enthusiasts to experiment with agent-based company management.
ai-agent-builder is an open-source Python package offering templates and tools for building AI agents. It helps developers automate workflows and create custom agents for various tasks, providing reusable components and integration with Python projects.
Agenthost AI Agent Factory is a web platform that allows users to create, customize, and deploy AI agents capable of integrating with over 2,000 apps. It offers features like custom actions, analytics, monetization, and team collaboration, targeting businesses and teams looking to automate workflows.
Agent Matters is an open-source Python package for building and managing AI agents. It provides a framework and CLI tools for developers to create, deploy, and orchestrate autonomous agents in Python environments.
agentdossier is an open-source Python SDK designed to help developers manage provenance, records, and anchoring for AI agent systems. It provides tools for tracking agent actions and maintaining reliable records, supporting transparency and auditability in agent-based workflows.
AgentMeet is a platform designed for real-time conversations between AI agents, enabling agent-to-agent communication in a shared virtual room. The service allows users to create a room with a single click, generating a shareable code that agents can use to join the conversation. No signup, OAuth, or API key is required, and agents participate via HTTP requests, making the platform accessible to any agent capable of making a POST request. This includes compatibility with various AI models such as Claude, GPT, and local large language models, as long as they can communicate over HTTP. The platform emphasizes simplicity and speed, allowing agents to join a meeting in as few as three lines of Python code or from any language or framework that supports HTTP. Users can watch AI agents converse, debate, and collaborate in real time, with applications highlighted such as agent onboarding, multi-agent debate, red-teaming for security testing, autonomous stand-ups, trading oversight, and consensus protocols. These use cases demonstrate the platform's utility for orchestrating complex decision-making, facilitating context handoff, and enabling collaborative workflows among multiple autonomous agents. AgentMeet is delivered as a web-based service with an API, requiring no SDK installation. The platform is positioned as a playground for AI agent collaboration, offering real-time visibility into agent interactions. The service is available for free, and open source availability is indicated as forthcoming. The tool is aimed at those interested in experimenting with or deploying multi-agent systems, providing a straightforward way to observe and manage agent conversations without the need for complex setup or integration. Overall, AgentMeet serves as a multi-agent conversation platform, streamlining agent-to-agent communication and supporting a range of collaborative and evaluative scenarios for AI agents.
dagent-ai is an open-source framework that allows developers to build, orchestrate, and manage autonomous AI agents using directed acyclic graphs (DAGs) with human review steps. It is designed for complex agent workflows and is distributed as a Python package for CLI and programmatic use.
Agent-Native is an open-source framework designed for building applications centered around AI agents, enabling developers to create agentic apps where agents and user interfaces are integrated at the core. The platform allows users to rapidly develop robust applications by providing a foundation that merges agent operations with full-featured UI, shared state, and database access. This approach aims to eliminate the traditional divide between apps and agents, offering a unified architecture where both can collaborate and evolve together. The framework supports a wide range of features tailored for building complex, customizable agent-native applications. Developers can define actions once and have them automatically exposed as UI actions, agent tools, HTTP endpoints, CLI commands, permission checks, and audit trails. Agent-Native includes built-in modules for notifications, recurring jobs, agent teams, monorepos, permissions (RBAC), organizations, workspace secrets, real-time sync, SQL state management, multi-tenancy, data loaders, live queries, and observability. The platform also offers integrations such as MCP (Multi-Channel Platform) apps, A2A (Agent-to-Agent) handoffs, human handoff, SSO, OAuth, and support for external agents. Additional features include audit logs, workspaces, privacy controls, skills, security, voice input, file uploads, analytics, experiments, feedback loops, and dashboards. The framework provides ready-to-fork example apps and toolkits, including solutions for screen recordings, meeting notes, coding agents with visual planning, Figma-based prototyping, Markdown editing, Google Slides generation, analytics dashboards, and chat applications. io. It is open source and forkable, allowing developers to own and customize their codebase. The platform is suitable for developers looking to build agentic SaaS tools, internal tools, or AI-powered applications that require deep integration between agents and user interfaces. The open-source nature of the framework ensures that users retain ownership and flexibility over their applications, with the ability to extend, modify, and deploy as needed.
