Project TTV MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Project TTV MCPInitialize the UV environment"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Project TTV MCP
This repository contains instructions for setting up and running an MCP service that can be published to PyPI.
Setup Instructions
1. Initialize UV Environment
uv init --build-backend "hatchling"
uv add "mcp[cli]"2. Create Project Structure
touch src/project_ttv_mcp/project_ttv_mcp.pyRelated MCP server: Hello World MCP Server
Package Development
To turn this MCP service into a Python package that can be published to PyPI:
Update
__init__.pyto include amain()function that runs MCPCreate a
__main__.pyscript that calls the main function and serves as an entry point
Running the Service
Local Development
You can run this MCP service as a module using either of these methods:
uv run -m project-ttv-mcpConfiguration Options
Local Configuration
{
"mcpServers": {
"Demo": {
"command": "uv",
"args": [
"--directory",
"/Users/ram/Documents/mcp-stdio",
"run",
"-m",
"project_ttv_mcp"
]
}
}
}GitHub Repository Configuration
Using uvx to install dependencies in a temporary environment:
{
"mcpServers": {
"Demo": {
"command": "uvx",
"args": [
"git+https://github.com/ramsrk7/mcp-stdio"
]
}
}
}This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ramsrk7/mcp-stdio'
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