Npcpy MCP Server
The python library for research and development in NLP, multimodal LLMs, Agents, ML, Knowledge Graphs, and more.
What is Npcpy MCP Server?
Npcpy MCP Server is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to python library for research and development in nlp, multimodal llms, agents, ml, knowledge graphs, and more.
The python library for research and development in NLP, multimodal LLMs, Agents, ML, Knowledge Graphs, and more.
This server falls under the AI/ML and Databases categories on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- The python library for research and development in NLP, mult
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx npcpyExamples
No examples available for this server.
Configuration
Configuration Details
claude_desktop_config.json
Not available
Security
Authentication
Features
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about Npcpy MCP Server
What is Npcpy MCP Server?
Npcpy MCP Server is a Model Context Protocol (MCP) server that python library for research and development in nlp, multimodal llms, agents, ml, knowledge graphs, and more. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Npcpy MCP Server?
Follow the installation instructions on the Npcpy MCP Server GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Npcpy MCP Server?
Npcpy MCP Server works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Npcpy MCP Server free to use?
Yes, Npcpy MCP Server is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Set Up Npcpy MCP Server in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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