Showing 4 open source projects for "agent ai"

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  • 1
    npcpy

    npcpy

    The AI toolkit for the AI developer

    npcpy is a Python-based agent framework and command-line toolkit (the NPC Shell) for developers to build, test, and integrate AI agents into their workflows, including both command-line and GUI interfaces via NPC Studio. Welcome to npcpy, the core library of the NPC Toolkit that supercharges natural language processing pipelines and agent tooling. npcpy is a flexible framework for building state-of-the-art applications and conducting novel research with LLMs. ...
    Downloads: 4 This Week
    Last Update:
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  • 2
    Nerve

    Nerve

    The Simple Agent Development Kit

    Nerve is a developer-friendly Agent Development Kit (ADK) that utilizes YAML and a CLI to define, run, orchestrate, and evaluate LLM-driven agents. It supports declarative setups, tool integration, workflow pipelines, and both MCP client and server roles. Nerve is a simple yet powerful Agent Development Kit (ADK) to build, run, evaluate, and orchestrate LLM-based agents using just YAML and a CLI. It’s designed for technical users who want programmable, auditable, and reproducible automation...
    Downloads: 8 This Week
    Last Update:
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  • 3
    mcp-use

    mcp-use

    A solution to build and deploy MCP agents and applications

    mcp-use is an open source development platform offering SDKs, cloud infrastructure, and a developer-friendly control plane for building, managing, and deploying AI agents that leverage the Model Context Protocol (MCP). It enables connection to multiple MCP servers, each exposing specific tool capabilities like browsing, file operations, or specialized integrations, through a unified MCPClient. Developers can create custom agents (via MCPAgent) that dynamically select the most appropriate...
    Downloads: 1 This Week
    Last Update:
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  • 4

    SynquoRum

    Multi-AI workspace with persistent cross-session memory via MCP

    SynquoRum is a multi-AI workspace for people who use multiple language models daily and are tired of fragmented context when switching tools. Most AI products treat memory as belonging to the model. Every new session starts from zero. SynquoRum inverts this: memory belongs to the workspace, not to any specific agent. Through an MCP (Model Context Protocol) server with 22 tools, the workspace exposes its memory to any MCP-compatible client — Claude.ai, Cursor, Cline, custom agents — so the same context follows you across providers and sessions. ...
    Downloads: 0 This Week
    Last Update:
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