npcpy is the premier open-source library for integrating LLMs and Agents into python systems.
npcpy is the premier open-source library for integrating LLMs and Agents into python systems.
npcpy is a library that provides key primitives for research and development with multimodal language models, agentic AI, and knowledge graphs. Its flexible framework makes it easy to engineer powerful AI applications with support for local (ollama, llama.cpp, omlx, LM Studio) and cloud providers. Build multi-agent teams and simplify context engineering through the NPC Context-Agent-Tool data layer which ensures compliance through software rather than prompts. bash pip install npcpy
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{
"mcpServers": {
"npcpy": {
"command": "uvx",
"args": ["npcpy"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
Read, search and edit files inside allowed directories with the Model Context Protocol reference Filesystem server.
Retrieve version-aware library documentation and code examples with Context7 MCP, using resolve-library-id and query-docs.
Persistent local memory for coding agents: temporal knowledge graph, procedural and episodic recall
SquatGuard MCP Template for Python
1. **请求(Request)**: 客户端向服务器发送一个JSON-RPC请求，例如`tool_run`，要求执行一个名为`read_file`的工具。 2. **分发(Dispatch)**: `server.py`中的MCP服务器核心接收请求，并将其分派给`ToolRegistry`。
AI coding agents spend most of their token budget *finding* code before they can *work on* it. They grep, read files, grep again, backtrack. On a