SonAgent is an extensible open-source framework designed for building, organizing, and running AI agents in Python. It provides core modules for memory storage, tool wrappers, planning logic, and asynchronous event handling. Developers can register custom tools, integrate language models, manage long-term agent memory, and orchestrate multiple agents to collaborate on complex tasks. SonAgent’s modular design accelerates the development of conversational bots, workflow automations, and distributed agent systems.

OpenKBS Apps provides a unified interface to upload and process documents, generate semantic embeddings, and configure multiple LLMs for retrieval-augmented generation. Users can fine-tune query workflows, set access controls, and integrate agents into web or messaging channels. The platform offers analytics on user interactions, continuous learning from feedback, and support for multilingual content, enabling rapid creation of intelligent assistants tailored to organizational data.

BabyAGI UI provides a streamlined, browser-based front end for the open-source BabyAGI autonomous agent. Users input an overall objective and initial task; the system then leverages large language models to generate subsequent tasks, prioritize them based on relevance to the main goal, and execute each step. Throughout the process, BabyAGI UI maintains a history of completed tasks, shows outputs for each run, and updates the task queue dynamically. Users can adjust parameters like model type, memory retention, and execution limits, offering a balance of automation and control in self-directed workflows.

dbt-llm-agent leverages large language models to transform how data teams interact with dbt projects. It empowers users to explore and query their data models using plain English, auto-generate SQL based on high-level prompts, and retrieve model documentation instantly. The agent supports multiple LLM providers—OpenAI, Cohere, Vertex AI—and integrates seamlessly with dbt’s Python environment. It also offers AI-driven code reviews, suggesting optimizations for SQL transformations, and can generate model tests to validate data quality. By embedding an LLM as a virtual assistant within your dbt workflow, this tool reduces manual coding efforts, enhances documentation discoverability, and accelerates the development and maintenance of robust data pipelines.

Kin Kernel is a lightweight, open-source kernel framework for constructing AI-powered digital workers. It provides a unified system for orchestrating large language models, managing contextual memory, and integrating custom tools or APIs. With an event-driven architecture, Kin Kernel supports asynchronous task execution, session tracking, and extensible plugins. Developers define agent behaviors, register external functions, and configure multi-LLM routing to automate workflows ranging from data extraction to customer support. The framework also includes built-in logging and error handling to facilitate monitoring and debugging. Designed for flexibility, Kin Kernel can be integrated into web services, microservices, or standalone Python applications, enabling organizations to deploy robust AI agents at scale.

LinkAgent provides a lightweight microkernel for building AI agents with pluggable components. Users can register language model backends, retrieval modules, and external APIs as tools, then assemble them into workflows using built-in planners and routers. LinkAgent supports memory handlers for context persistence, dynamic tool invocation, and configurable decision logic for complex multi-step reasoning. With minimal code, teams can automate tasks like QA, data extraction, process orchestration, and report generation.

MCP Agent provides a robust foundation for building intelligent AI-driven assistants by offering modular components for integrating language models, custom tools, and data sources. Its core functionalities include dynamic tool invocation based on user intents, context-aware memory management for long-term conversations, and a flexible plugin system that simplifies extending capabilities. Developers can define pipelines to process inputs, trigger external APIs, and manage asynchronous workflows, all while maintaining transparent logs and metrics. With support for popular LLMs, configurable templates, and role-based access controls, MCP Agent streamlines the deployment of scalable, maintainable AI agents in production environments. Whether for customer support chatbots, RPA bots, or research assistants, MCP Agent accelerates development cycles and ensures consistent performance across use cases.

Memor offers a memory subsystem for language model agents, allowing them to store embeddings of past events, user preferences, and contextual data in vector databases. It supports multiple backends such as FAISS, ElasticSearch, and in-memory stores. Using semantic similarity search, agents can retrieve relevant memories based on query embeddings and metadata filters. Memor’s customizable memory pipelines include chunking, indexing, and eviction policies, ensuring scalable, long-term context management. Integrate it within your agent’s workflow to enrich prompts with dynamic historical context and boost response relevance over multi-session interactions.

Officely AI provides a robust automation workflow builder that enables users to design AI workflows easily. The platform allows the integration of AI agents that can interact with customers through channels like Zendesk, Intercom, and WhatsApp. Users can leverage multiple Large Language Models (LLMs) to create dynamic agents catered to specific business needs. It supports various use cases from customer support automation to lead qualification, thereby improving operational efficiency and user experience.

scenario-go serves as a robust framework for constructing AI agents in Go by allowing developers to author scenario definitions that specify step-by-step interactions with large language models. Each scenario can incorporate prompt templates, custom functions, and memory storage to maintain conversational state across multiple turns. The toolkit integrates with leading LLM providers via RESTful APIs, enabling dynamic input-output cycles and conditional branching based on AI responses. With built-in logging and error handling, scenario-go simplifies debugging and monitoring of AI workflows. Developers can compose reusable scenario components, chain multiple AI tasks, and extend functionality through plugins. The result is a streamlined development experience for building chatbots, data extraction pipelines, virtual assistants, and automated customer support agents fully in Go.

SWE-agent is a developer-focused AI agent framework that integrates with GitHub to autonomously diagnose and resolve code issues. It runs in Docker or GitHub Codespaces, uses your preferred language model, and allows you to configure tool bundles for tasks like linting, testing, and deployment. SWE-agent generates clear action trajectories, applies pull requests with fixes, and provides insights via its trajectory inspector, enabling teams to automate code review, bug fixing, and repository cleanup efficiently.

WebextLLM is the first browser extension designed to seamlessly integrate large language models into web applications. This innovative tool runs LLMs in an isolated environment, ensuring security and efficiency. Users can utilize the powerful capabilities of AI for various tasks, such as content generation, summarization, and interactive conversations directly from their browser, simplifying the process of AI interaction in daily tasks and enhancing workflow.

Twilio AI Assistants is a cloud-based platform that empowers businesses to build custom conversational agents powered by state-of-the-art large language models. These AI assistants can handle multi-turn dialogues, integrate with backend systems via function calls, and communicate across SMS, WhatsApp, voice calls, and web chat. Through a visual console or APIs, developers can define intents, design rich message templates, and connect to databases or CRM systems. Twilio ensures reliable global delivery, compliance, and enterprise-grade security. Built-in analytics track performance metrics like user engagement, fallback rates, and conversational paths, enabling continuous improvement. Twilio AI Assistants accelerates time-to-market for omnichannel bots without managing infrastructure.

AgentRails empowers Rails developers to build intelligent agents that leverage large language models for natural language understanding and generation. Developers can define custom tools and workflows, maintain conversation state across requests, and integrate seamlessly with Rails controllers and views. It abstracts API calls to providers like OpenAI and enables rapid prototyping of AI-driven features, from chatbots to content generators, while adhering to Rails conventions for configuration and deployment.

AgentX provides an extensible architecture for building AI-driven agents that leverage large language models, tool and API integrations, and memory modules to perform complex tasks autonomously. It features a plugin system for custom tools, support for vector-based retrieval, chain-of-thought reasoning, and detailed execution logs. Users define agents through flexible configuration files or code, specifying tools, memory backends like Chroma DB, and reasoning pipelines. AgentX manages context across sessions, enables retrieval-augmented generation, and facilitates multiturn conversations. Its modular components allow developers to orchestrate workflows, customize agent behaviors, and integrate external services for automation, research assistance, customer support, and data analysis.

AnythingLLM provides a comprehensive solution for leveraging AI without relying on internet connectivity. This application supports the integration of various large language models (LLMs) and allows users to create custom AI agents tailored to their needs. Users can chat with documents, manage data locally, and enjoy extensive customization options, ensuring a personalized and private AI experience. The desktop application is user-friendly, enabling efficient document interactions while maintaining the highest data privacy standards.

BotSquare is a low-code AI app development platform that empowers users to create and deploy AI bots with ease. It allows seamless multi-channel deployment, letting AI applications go live across WeChat, websites, SMS, and other spaces instantly. The platform is user-friendly and caters to different industries by offering a diverse range of AI modules. Users can customize AI solutions by dragging and dropping modules, linking documents, and integrating Large Language Models (LLMs). BotSquare's mission is to revolutionize app development by simplifying the overall process.

ChainStream is a cross-platform mobile and desktop inference framework that streams partial outputs from large language models in real time. It breaks LLM inference into submodel chains, enabling incremental token delivery and reducing perceived latency. Developers can integrate ChainStream into their apps using a simple C++ API, select preferred backends like ONNX Runtime or TFLite, and customize pipeline stages. It runs on Android, iOS, Windows, Linux, and macOS, allowing for truly on-device AI-driven chat, translation, and assistant features without server dependencies.

Chipper is a fully open-source React component library designed to simplify the creation of conversational interfaces powered by large language models. It offers real-time streaming of AI responses, built-in context and history management, support for multiple agents in a single chat, file attachments, and theme customization. Developers can integrate any LLM backend via simple props, extend with plugins, and style using CSS-in-JS for seamless branding and responsive layouts.

ChromeAI is a local AI assistant built to run seamlessly within the Chrome browser. It harnesses advanced language models to facilitate smooth interactions, from generating text to providing concise answers in real-time. This built-in AI offers local processing, ensuring user privacy while delivering a powerful tool that can improve productivity in daily browsing activities. Whether you need instant search assistance or help with writing, ChromeAI is designed to enhance your web experience significantly.