Void MCP Server
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About Void MCP Server
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Config
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Overview
What is Void MCP Server?
Void MCP Server is a Model Context Protocol (MCP) server for managing LLM context data. It includes a utility run_local.py that can launch a local Hugging Face model and a Streamlit interface.
How to use Void MCP Server?
Install dependencies (npm install for Node, pip install -r requirements.txt for Python), then build with npm run build. Use python run_local.py --model sshleifer/tiny-gpt2 --port 8000 to run a local model, or streamlit run app.py for the Streamlit UI.
Key features of Void MCP Server
- MCP server for managing LLM context data
- Local Hugging Face model launch via
run_local.py - Streamlit UI for interaction
- Supports Node and Python development
- Tests available via
npm testandpytest
Use cases of Void MCP Server
- Running a local LLM for context management experiments
- Prototyping MCP-based context-aware applications
- Testing and debugging MCP server implementations
FAQ from Void MCP Server
What does Void MCP Server do?
It provides a Model Context Protocol (MCP) server for managing LLM context data, plus a utility to launch a local Hugging Face model and a Streamlit interface.
What are the dependencies?
Node (for the MCP server) and Python (for the local model and Streamlit UI). Install them via npm install and pip install -r requirements.txt.
How do I run the local model?
Run python run_local.py --model sshleifer/tiny-gpt2 --port 8000 to launch a local Hugging Face model on port 8000.
How do I start the Streamlit interface?
Use the command streamlit run app.py in the project root directory.
How can I test the server?
Node tests: npm test. Python tests: pytest.
Frequently asked questions
What does Void MCP Server do?
It provides a Model Context Protocol (MCP) server for managing LLM context data, plus a utility to launch a local Hugging Face model and a Streamlit interface.
What are the dependencies?
Node (for the MCP server) and Python (for the local model and Streamlit UI). Install them via `npm install` and `pip install -r requirements.txt`.
How do I run the local model?
Run `python run_local.py --model sshleifer/tiny-gpt2 --port 8000` to launch a local Hugging Face model on port 8000.
How do I start the Streamlit interface?
Use the command `streamlit run app.py` in the project root directory.
How can I test the server?
Node tests: `npm test`. Python tests: `pytest`.
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