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Alternatives
Software like openloom
What else does this job. Matched on what each project does, not on who links to whom.
Closest first
- loom-harnesspypi.orgloom-harness is an open-source CLI tool that provides an agent harness for reading, replaying, and rewinding agent actions. It is designed for AI developers working with agentic systems, supporting debugging and analysis, and integrates with Anthropic's Claude.
- easyloopspypi.orgeasyloops is an open-source agent harness for integrating and orchestrating autonomous AI agents with open models. It provides planning, looping, verification, and deployment tools, supporting local inference and OpenAI-compatible workflows for AI developers and researchers.
- Openloomuseopenloom.comOpenloom is a web application that uses AI to process Loom video recordings directly in the browser. It generates timestamped screenshots, transcripts, and structured documents for further use, ensuring privacy and convenience for knowledge workers and teams.
- OpenLoomiopenloomi.aiOpenLoomi is an open-source, local-first AI workspace designed to provide persistent memory and context for users' work. It connects to tools like Slack, email, and docs, enabling AI agents to understand ongoing projects, decisions, and follow-ups. Ideal for teams and builders seeking privacy and seamless AI integration.
- luteloopspypi.orgluteloops is an open-source CLI tool designed for developers to build, automate, and manage AI coding agents. It provides a framework for agent orchestration and automation, supporting advanced workflows for AI-driven coding tasks. The tool is suitable for developers seeking to streamline agent-based automation.
- red-standard-loompypi.orgred-standard-loom is a CLI-based agent loop engine that enables running autonomous AI agents powered by local models. It supports Ollama, LM Studio, Hugging Face, MLX, and any OpenAI-compatible server. Ideal for developers building offline or privacy-focused LLM agent applications.
- OpenHarnessopen-harness.devOpenHarness is an open-source toolkit designed for building AI agents in code, offering developers composable and stateless primitives to create agent harnesses similar to Claude Code-like products. It provides a TypeScript SDK that enables full control over agent behavior, message history, and state management, allowing users to inspect, modify, or share state between agents as plain arrays. The platform is built on top of the Vercel AI SDK, supporting integration with model providers such as OpenAI, Anthropic, Google, or any compatible provider. Key features of OpenHarness include composable middleware for functionalities like turn tracking, retries, context compaction, and persistence, which can be mixed and matched as needed. Developers can implement subagent hierarchies, delegating tasks to specialized child agents with background execution and Promise-like combinators. The toolkit also supports automatic two-phase context management, which involves pruning old tool results and applying LLM-powered summarization to maintain relevant context for the agents. Tool permissions can be managed through asynchronous approval callbacks, enabling gating of tool execution in various interfaces including CLI prompts, web modals, or external services. OpenHarness also offers integration with the Model Context Protocol (MCP), allowing connection to any MCP server via standard input/output, HTTP, or SSE transport. md files. The SDK is compatible with both web and CLI environments, providing React hooks, Vue composables, and streaming support to build agents for any runtime. js or edge runtimes. OpenHarness is released under the MIT License and developed by MaxGfeller, emphasizing its open-source nature and flexibility for developers seeking to construct advanced, customizable AI agent systems.
- Open Agent Loopsfeatherless.aiOpen Agent Loops is a minimal, provider-agnostic framework designed for building agent loops, focusing on modularity and flexibility. The tool is structured around swappable interfaces for key components such as models, memory, tools, and stop conditions, allowing developers to substitute implementations without changing the core logic. It operates headlessly by default, emitting typed event streams rather than rendering output, so users can integrate their own front ends or consume the data in various formats including CLI, DOM timelines, or raw JSONL. The framework exposes a concise API surface, centering on the runAgent function. Developers can define tools—each with a name, description, parameter schema, and execution function—and pass them into the agent loop. The memory interface is also modular, with implementations such as SessionMemoryStore available and the ability to swap to alternatives like Redis. The model interface is compatible with any endpoint that supports the OpenAI chat-completions wire format, and the evidence lists open-model families such as DeepSeek, GLM, Qwen, Kimi, MiniMax, and Gemma as being exercised with the framework. Tool calls can run in parallel, and results are folded back into the loop. Stop conditions are configurable, allowing the agent to halt on criteria such as a maximum number of steps or a custom predicate. Streaming is a core feature, with the stream() method returning an async iterable of events, including reasoning, text, and tool calls, delivered incrementally. The tool supports optional hooks for extending behavior, such as gating tool calls or reshaping context. Additional composable building blocks are mentioned, including skills (bundled instructions and tools), planning tools (durable working memory and workflow freezing), composable agents (sub-agents callable as tools), and channels for integrating live transports like Slack or Discord. Open Agent Loops is delivered as a universal ESM package with a single dependency (zod), running in environments such as Node, Bun, Deno, and browsers. The evidence does not specify pricing or licensing details.
Ranked by how close each one sits to openloom in the index, not by popularity. Back to openloom →