Open-source alternatives to Atomic Agents

Screenpipe is a local screen and audio recorder that captures and indexes digital activity to create a searchable archive of computer usage. It functions as an AI context engine, providing a local database of visual and auditory history to ground large language models. The system serves as a Model Context Protocol server, delivering screen history and meeting transcriptions to external AI assistants. It utilizes an OCR screen search tool to extract text from visual data and a speech-to-text transcription tool for identifying speakers in system and microphone audio. The software includes capa

Yao is an LLM agent framework and low-code web app builder designed for orchestrating autonomous AI agents. It provides a platform to design, deploy, and coordinate agents with specialized personas that can plan tasks, utilize external tools, and execute multi-stage pipelines. The project distinguishes itself through a Model Context Protocol server for connecting assistants to external binaries and HTTP services, and a gRPC remote execution engine that allows agents to manage remote servers and devices. It includes a model-agnostic provider bridge that supports dynamic switching between vario

Miroflow is an agent orchestration framework designed to coordinate multiple large language models and autonomous agents to perform complex research and reasoning tasks. It functions as a hierarchical workflow manager that distributes workloads across specialized agents using intent recognition and structured planning to gather deep information and solve challenging queries. The system distinguishes itself through a multi-model integration gateway and a provider-agnostic interface, allowing it to unify various language model providers. It extends these models via a tool-augmented framework th

Llama-stack is a standardized orchestration stack and generative AI API gateway. It provides a unified communication layer and a consistent interface for deploying, managing, and interacting with various large language model providers and deployments. The system functions as an agent framework that manages tool execution and versioned skill bundles to automate complex tasks. It includes a batch processing system for handling large volumes of asynchronous requests through offline processing and a vector database interface for storing and searching documents to enable retrieval augmented genera

Maid is a mobile large language model chat client and local runner. It provides a unified interface for interacting with AI models via cloud APIs or by executing model files directly on mobile hardware for offline generation. The project functions as a multi-provider manager that handles API keys and a system for downloading and loading curated model files to the device. It utilizes a provider-agnostic interface to allow switching between local and remote backends. The application includes tools for organizing and exporting chat histories, synchronizing user data across multiple devices, and

Axonhub is an AI gateway and multi-model API proxy that provides a unified interface for routing requests to multiple large language model providers. It functions as a load balancer and translation layer, converting a standardized API format into provider-specific payloads to enable communication with various AI models without provider-specific code. The system manages traffic through rule-based routing and automatic failover to maintain high availability. It differentiates its operations by providing a provider-agnostic interface that decouples client requests from specific model backends us

LangChainJS is an AI agent orchestrator and application framework designed for building autonomous systems that use large language models to plan and execute tasks. It serves as an integration library that connects language models with tools, memory, and external data sources to create context-aware logic and complex workflows. The project provides a provider-agnostic interface and model provider abstraction, allowing applications to switch between different language model providers without rewriting core logic. It includes a toolkit for retrieval augmented generation, utilizing retrievers to

OpenCompass is a comprehensive evaluation platform, benchmarking suite, and distributed model evaluator designed to measure the performance and accuracy of large language models. It provides a framework for benchmarking both open-source and API-based models against diverse datasets using standardized metrics and reproducible pipelines. The project features an automated judging framework that uses language models as judges to score and verify the quality of generated text. It includes a performance leaderboard system for comparing the relative capabilities of various models across industry-sta

OpenClawChineseTranslation is a framework for building conversational assistants that functions as a cross-platform chat gateway. It synchronizes conversational data between multiple external messaging applications and a centralized core, allowing users to interact with an assistant across different platforms. The system utilizes a plugin-based extension architecture to integrate external services such as note-taking and password managers. It features a model-agnostic provider interface, which enables the underlying intelligence to be swapped by selecting different large language model provid

Codegraph is a local codebase indexer and static analysis graph database that serves as a context provider for AI agents. It parses multiple programming languages into a searchable knowledge graph of symbols and dependencies, exposing these relationships to AI tools through the Model Context Protocol. The project distinguishes itself by aggregating relevant code snippets and symbol flows to reduce token usage for large language models. It automates the configuration of server settings and steering instructions across various AI agent platforms and command line editors to enable automatic code

Open Canvas is a system for managing stateful AI agent workflows through a collaborative editor and orchestration framework. It provides a shared workspace where humans and large language models co-author documents and write code in real time, supported by a structured text editor with live rendering. The project distinguishes itself by integrating a state manager that tracks session context, user memories, and historical snapshots across conversational threads. It employs a durable execution model that allows for human-in-the-loop interventions and maintains a version tracking system for doc

This project is a messaging bot bridge and multi-model AI gateway that connects large language models to platforms such as QQ, Telegram, and WeChat. It functions as an AI agent workflow engine, enabling the automation of private and group chat interactions across multiple social communication channels. The system features a multimodal chat interface capable of processing and sending text, voice, and AI-generated images. It includes a web-based management dashboard for administering AI model configurations, monitoring activity, and designing custom bot personalities and persona presets to cont

Maestro is an autonomous task workflow engine that decomposes high-level goals into hierarchical sub-tasks and orchestrates their execution using multiple language model agents. It provides a unified interface for routing requests across different LLM providers, including proprietary models like Anthropic, OpenAI, and Gemini, as well as local models, enabling flexible provider selection and switching through a single entry point. The system distinguishes itself through its ability to generate complete software project structures directly on the host machine, creating directories and source fi

This project is a knowledge base plugin and RAG context manager that uses a local vector database interface to enable semantic search and relationship mapping. It transforms text into numerical vectors to find semantically related notes and excerpts based on conceptual meaning rather than keyword matches. The system differentiates itself through a semantic graph visualizer that maps notes into clusters to reveal conceptual connections. It also features a context manager capable of bundling local notes and excerpts into reusable packs to provide grounded factual bases for large language model

mcp-agent is a framework for building AI agents that integrate with Model Context Protocol servers to execute tools and access data. It functions as a multi-agent orchestrator and protocol-compliant server, enabling the creation of agents that can discover and invoke tools from connected external servers. The project distinguishes itself through a durable workflow engine that supports long-running tasks capable of pausing, resuming, and surviving restarts. It implements complex orchestration patterns, including iterative evaluator-optimizer loops, hierarchical workflow nesting, and specialist

Pi is an autonomous coding agent and framework for building AI agents capable of executing independent loops. It functions as an agent state management system that tracks and persists tool calls throughout complex workflows, utilizing a command-line interface for interaction and control. The system features a self-extensible design, allowing agents to write and implement new capabilities and tools into their own runtime environment. It also includes a provider-agnostic abstraction layer that standardizes interactions across different large language model providers through a unified API. The

This project is a conversational assistant and retrieval-augmented generation system designed to provide technical answers from official documentation and support knowledge bases. It implements a retrieval architecture that routes queries through specialized tools and utilizes a model abstraction layer to switch between different chat and embedding providers without modifying core integration code. The system employs a graph-based state machine for durable agent execution, enabling state persistence and human-in-the-loop interactions. It features an agentic middleware framework that allows fo

gpt-crawler is a web scraping utility designed to extract website content and convert it into structured text files for use as AI model knowledge bases. It functions as a data generator that crawls specified web addresses to produce the knowledge files required for building custom GPTs, grounding large language models, and providing context to AI agents. The system transforms raw HTML into clean Markdown text to reduce token usage and improve readability for AI models. It utilizes token-aware content chunking and output file size limitations to ensure generated datasets remain compatible with

Local Deep Research is an autonomous research system consisting of an LLM research agent, a local model orchestrator, and a multi-engine search aggregator. It is designed to execute deep research by decomposing complex questions into atomic facts and synthesizing cited reports from academic, technical, and private document sources. The system features an encrypted research workspace that ensures zero-knowledge privacy through isolated, per-user encrypted databases. It utilizes a local RAG knowledge base to index research sources into searchable vector stores, allowing for retrieval-augmented

rlm is an LLM code execution engine and orchestration framework designed to coordinate multiple language model calls and recursive sub-tasks through a programmable environment. It provides a sandboxed REPL environment and a recursive context processor to handle inputs that exceed standard token limits by programmatically decomposing prompts. The project differentiates itself through a reinforcement learning training harness used to teach models how to utilize recursive calls and code execution. It includes a reasoning visualization system that records and renders execution trajectories to ana

This project is a Telegram bot that integrates large language models, such as OpenAI and Claude, to provide an AI chat interface within the messaging app. It functions as a multi-model AI gateway that routes prompts to various providers via API keys and YAML configurations. The implementation includes a provider-agnostic routing system and response streaming to deliver text word-by-word. It distinguishes itself with a token-based cost tracker that calculates the monetary expenditure of API requests and a whitelist-based access control system to restrict usage to authorized users. The bot sup

Ruoyi AI is a multi-agent orchestration platform that coordinates specialized AI agents through a supervisor-based delegation pattern, allowing complex requests to be broken into subtasks that are assigned, executed, and merged under centralized control. It provides a unified abstraction layer that connects multiple AI model providers behind a single interface, so switching between providers requires no application code changes. The platform also includes a retrieval-augmented generation engine that indexes internal documents into vector stores and retrieves relevant context at query time to g

This project is an extension for JupyterLab that integrates large language model providers and AI agents directly into computational notebooks. It functions as an integration layer and orchestrator, bridging generative AI backends with a data science workspace to enable the execution of AI prompts within notebook cells and the insertion of generated code blocks into documents. The system features a collaborative chat interface where multiple users can engage with AI personas in real time, sharing conversation threads and utilizing drag-and-drop file attachments for context. It allows for the

AutoAgent is a multi-agent orchestrator and natural language workflow builder designed to connect multiple large language models with external API tools. It provides a framework for designing multi-step agent interactions and reasoning processes using plain text instead of manual code. The platform functions as a tool integration gateway, linking agents to third-party platforms and authenticated browser sessions. It enables the execution of complex analytical tasks and deep research by distributing work across collaborative agent frameworks and importing browser cookies to access restricted w

This project is a software development kit and framework for building AI agent orchestration, session management, and tool integration systems. It provides a backend infrastructure for hosting remote AI sessions and coordinating multi-agent workflows using large language models. The SDK enables the definition of specialized agents and the orchestration of complex tasks through parallel workstreams. It distinguishes itself by offering a multi-tenant backend capable of horizontal scaling and a headless server runtime that separates session execution from the client interface. The system covers

This project is a framework for managing generative AI services through a unified provider interface and adapter layer. It provides a standardized API for calling multiple cloud-based and locally hosted models, translating provider-specific parameters and responses into a uniform format. The system includes an agent orchestrator designed for long-running tasks, featuring state persistence for resuming runs and execution tracing to monitor decision-making processes. It integrates the Model Context Protocol to connect models to external servers and filesystems and employs a policy-based executi

This project is a multi-protocol API simulation and mocking system designed to replace external dependencies during development and testing. It provides an API mocking server, a network traffic proxy, and specialized simulators for language model services and identity providers. The system distinguishes itself through deep AI simulation capabilities, including the emulation of language model providers and Model Context Protocol servers using JSON-RPC 2.0. It supports multi-turn conversational logic, state tracking for AI chat APIs, and the visualization of agent execution through call graphs