langgraph-bigtool — Agent Tool by langchain-ai

by langchain-ai · Agent Tool · ★ 545

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About langgraph-bigtool

langgraph-bigtool is a Python library for creating LangGraph agents that can access large numbers of tools. It leverages LangGraph's long-term memory store to allow an agent to search for and retrieve relevant tools for a given problem. Features 🧰 Scalable access to tools: Equip agents with hundreds or thousands of tools. 📝 Storage of tool metadata: Control storage of tool descriptions, namespaces, and other information through LangGraph's built-in persistence layer. Includes support for in-memory and Postgres backends. 💡 Customization of tool retrieval: Optionally define custom functions for tool retrieval. This library is built on top of LangGraph, a powerful framework for building agent applications, and comes with out-of-box support for streaming, short-term and long-term memory and human-in-the-loop. Installation bash p

Quick Facts

Stars545
Forks44
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score65.7065146773357/100
Open Issues12
Last Updated2026-06-28
Created2025-03-03
Platformspython
Est. Tokens~15k

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Frequently Asked Questions

What is langgraph-bigtool?

langgraph-bigtool is Build LangGraph agents with large numbers of tools. It is categorized as a Agent Tool with 545 GitHub stars.

What programming language is langgraph-bigtool written in?

langgraph-bigtool is primarily written in Python.

How do I install or use langgraph-bigtool?

You can find installation instructions and usage details in the langgraph-bigtool GitHub repository at github.com/langchain-ai/langgraph-bigtool. The project has 545 stars and 44 forks, indicating an active community.

What license does langgraph-bigtool use?

langgraph-bigtool is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to langgraph-bigtool?

The top alternatives to langgraph-bigtool on Agent Skills Hub include skills, claude-forge, excalidraw-diagram-skill. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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