A four-pane neurosymbolic development environment (eNSAID) designed as a cognitive-relief layer for human-machine co-orbit. Built on AffineScript (TEA architecture) and Ephapax (Gossamer webview), wit
Potencia tu agente
Instalación del publicador. No es un endpoint de PlugMCP.
Host a copy with our keys and logs.
Aún no hay una versión empaquetada en el registro. Sigue el README del repositorio.
¿URL remota o un comando en tu máquina? En qué se diferencian las dos instalaciones
Ejecutar en PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
AbrirResumen general
A four-pane neurosymbolic development environment (eNSAID) designed as a cognitive-relief layer for human-machine co-orbit. Built on AffineScript (TEA architecture) and Ephapax (Gossamer webview), with friction monitoring (Vexometer), neural output gating (Anti-Crash); planned TypeLL (type) and ECHIDNA (proof) verification for the symbolic layer.
Herramientas
Aún no hay lista de herramientas. Los servidores remotos la reciben tras la primera comprobación de estado.
Preguntas frecuentes
Copia en esta página la configuración stdio para Cursor, Claude Desktop, Claude Code o VS Code. Usa la instalación del publicador, no un proxy de PlugMCP.
Este registro no indica ninguna variable de entorno obligatoria.
Panll se ejecuta localmente por stdio.
Última comprobación: 2026-11-11. A four-pane neurosymbolic development environment (eNSAID) designed as a cognitive-relief layer for human-machine co-orbit. Built on AffineScript (TEA architecture) and Ephapax (Gossamer webview), with friction monitoring (Vexometer), neural output gating (Anti-Crash); planned TypeLL (type) and ECHIDNA (proof) verification for the symbolic layer.
Del publicador
El README aún no se ha rastreado. Abrir el repositorio
A four-pane neurosymbolic development environment (eNSAID) designed as a cognitive-relief layer for human-machine co-orbit. Built on AffineScript (TEA architecture) and Ephapax (Gossamer webview), with friction monitoring (Vexometer), neural output gating (Anti-Crash); planned TypeLL (type) and ECHIDNA (proof) verification for the symbolic layer.