eko

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Eko is a production-ready JavaScript framework designed to let developers create reliable agentic workflows using natural language. It provides a unified interface to run agents both in browser and Node.js environments and supports building solutions that range from simple single-step commands to complex multi-step orchestrations. The repository aims to enable multi-agent applications with tool and agent customization, dynamic LLM selection, human-in-the-loop intervention points, and integration with MCP servers for inter-process coordination. Primary use cases shown include browser automation and web scraping, system file and process management, GUI automation, workflow automation, data processing and organization, and other multi-step task orchestrations. The project is open source and distributed under the MIT License.

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4315

App URL

https://github.com/FellouAI/eko

Github Repository

https://github.com/FellouAI/eko/blob/main/README.md

Features

Eko"s README highlights a set of practical features: pure JavaScript implementation for browser and Node.js, native multi-agent support, one-line agent and tool customization, native MCP connectivity, and configurable LLM providers and models. It calls out human-in-the-loop intervenability, stream planning for dynamic rendering, loop and listener task constructs for repetitive automation, and task parallelism. The framework advertises access to private web resources and a focus on development efficiency and task complexity. The package can be installed via pnpm and examples in the README show provider configurations for multiple LLMs to balance speed and performance.

Use Cases

Eko helps teams accelerate development of production agent workflows by providing a consistent API for cross-environment deployment, reducing friction when building multi-step, multi-agent tasks. Developers can orchestrate parallel agents, plug in different LLM providers and models, and add human checkpoints to intervene during execution. The framework supports automating browser interactions, scraping, file and process management, GUI automation, and structured data processing, which reduces boilerplate and coordination code. Integration with MCP servers enables scaled or distributed coordination. The README also surfaces security guidance, warning against embedding API keys in frontend code and recommending backend proxies for secrets protection.

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