awesome ai agents

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Basic Information

This repository is a curated, community-maintained directory of AI agents and agent-related projects. It aggregates both open-source projects and commercial offerings and organizes them by category, use case and capabilities. Each entry includes a short description, tags, category labels, and links to upstream repositories, documentation, demos, papers and other signals. The list is intended as a discovery and reference resource for engineers, researchers, product builders and evaluators who want to survey the AI agents landscape, compare platforms, frameworks, tools and turnkey agent products, or find examples and demos. The README also documents submission procedures, a web UI view, a landscape image, and notes about integrations and sandbox support where applicable. The project accepts pull requests and community contributions to keep the catalog current.

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Categorization

App Details

Features
Comprehensive, categorized catalog split into open-source projects and closed-source companies. Entries include a one-line description, fuller feature bullets, supported models or stacks when listed, links to GitHub, documentation, demos, papers and social channels, and screenshots or logos when available. Navigation aids include an alphabetized structure, a web UI version for filtering, a landscape image summarizing the space, and a submission form for new entries. The README records commit history and updates. It highlights integrations and sandbox notes for select projects and groups tooling by developer-focused frameworks, multi-agent platforms, agent builders, coding assistants and vertical applications. The file emphasizes community contributions and contribution guidelines.
Use Cases
The repository helps readers quickly discover and compare AI agents across many domains and technical categories. It reduces search overhead by centralizing links, short descriptions, supported stacks and notable features so teams can shortlist frameworks, SDKs, or turnkey products for evaluation. Researchers can find papers and demos, developers can find repos and install instructions, and product teams can spot vendors, integration notes and example use cases. The collection also documents agent types (multi-agent frameworks, code assistants, RPA and domain-specific agents), making it easier to match a tool to a project requirement. Community contributions and a web UI make it practical to keep the list up to date and share curated collections inside teams.

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