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Tiger

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Basic Information

Tiger is a community-driven, reusable and integrated tool ecosystem designed to connect LLM agents to real computer actions and external services. It uses the Upsonic platform for isolated tool storage, profiling and automatic documentation generation. The project provides a curated public library of agent tools and a workflow to create private on-prem Tiger instances via an Upsonic Docker deployment. Tiger makes it possible for agents to write and execute code, perform web searches, interact with the system clipboard, control applications and input devices, and use communication channels such as Telegram. It is intended to be framework-agnostic and to expose tools via a function call mechanism so that crewAI, LangChain, AutoGen and similar agent frameworks can share and invoke the same toolset. The repository is presented as a free, open MIT-licensed tool collection maintained by the community.

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App URL
https://github.com/Upsonic/Tiger
Github Repository
https://github.com/Upsonic/Tiger/blob/main/README.md

App Details

Features
Tiger exposes a structured tools library organized under a tools folder with many ready functions including app open/close, browser open_url, interpreter modules for python and shell (package checks, install, execute), search tools (google, duckduckgo, read_website), system queries (os_name, architecture, python_version), clipboard operations, knowledge store functions (put, pull, delete, index, reset) and Telegram as_user operations (signin, send_message, get_last_messages, delete_message). It provides integrations and examples for crewAI, LangChain and AutoGen agents and shows how to retrieve Tiger tools using the upsonic Python client. There is a public dashboard and auto-generated documentation for functions, resource usage metrics and a process to contribute new tools via pull requests. The README documents installation (pip3 install upsonic) and a Python 3.8+ requirement.
Use Cases
Tiger standardizes access to a broad set of agent-executable utilities so developers can equip LLM agents with consistent capabilities across frameworks. By centralizing tools and documentation on Upsonic, Tiger reduces integration effort when connecting agents to system actions, code execution and web interactions. Examples for crewAI, LangChain and AutoGen demonstrate how to plug the Tiger toolset into common agent workflows. The public dashboard allows inspection of available functions and their runtime characteristics, while an on-prem Upsonic option supports private deployments. Contributors can add tools through a prescribed format so the community can grow the library. Built-in Telegram signin and communication helpers enable agents to interact with users or services directly.

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