Install
The installation steps are in the documentation below. Documentation
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
memvid-mcp-server
A Streamable-HTTP MCP Server that uses memvid to encode text data into videos that can be quickly looked up with semantic search.
Supported Actions:
add_chunks: Adds chunks to the memory video. Note: each time you add chunks, it resets the memory.mp4. Unsure if there is a way to incrementally add.search: queries for the top-matching chunks. Returns 5 by default, but can be changed with top_k param.
Running
Set up your environment:
python3.11 -m venv my_env
. ./my_env/bin/activate
pip install -r requirements.txt
Run the server:
python server.py
With a custom port:
PORT=3002 python server.py
Connect a Client
You can connect a client to your MCP Server once it's running. Configure per the client's configuration. There is the mcp-config.json that has an example configuration that looks like this:
{
"mcpServers": {
"memvid": {
"type": "streamable-http",
"url": "http://localhost:3000"
}
}
}
Acknowledgements
- Obviously the modelcontextprotocol and Anthropic teams for the MCP Specification. https://modelcontextprotocol.io/introduction
- HeyFerrante for enabling and sponsoring this project.
Frequently asked questions
What is Memvid MCP Server?
Local server for memvid storage and semantic search.
How do I install Memvid MCP Server?
Follow the installation steps in its documentation, shown on this page and in its repository.
Is Memvid MCP Server open source?
Its code is public on GitHub, but the repository does not declare a standard license.
Who maintains Memvid MCP Server?
It is published by ferrants. AI.tn lists it but does not maintain or endorse it.
From the community awesome-mcp-servers lists and the project's GitHub repository. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.