VV knowledge layer for AI agents — MCP server exposing Visualize Value frameworks, voice, and content
Setup
Choose your client, copy the config, then fill in any required environment variables.
claude mcp add vvriter -- npx vvriter~/.codex/config.toml
[mcp_servers.vvriter]
command = "npx"
args = ["vvriter"]
# codex mcp add vvriter -- npx vvriter~/.cursor/mcp.json
{
"mcpServers": {
"vvriter": {
"command": "npx",
"args": [
"vvriter"
]
}
}
}.vscode/mcp.json
{
"servers": {
"vvriter": {
"type": "stdio",
"command": "npx",
"args": [
"vvriter"
]
}
}
}~/.gemini/settings.json
{
"mcpServers": {
"vvriter": {
"command": "npx",
"args": [
"vvriter"
]
}
}
}claude_desktop_config.json
{
"mcpServers": {
"vvriter": {
"command": "npx",
"args": [
"vvriter"
]
}
}
}.trae/mcp.json
{
"mcpServers": {
"vvriter": {
"command": "npx",
"args": [
"vvriter"
]
}
}
}