rar-agent-finder
Find a free, ready-made AI agent for a task in the public RAPP Agent Registry.
¿Debería usar esto?
Calidad y seguridad
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
Instalar
Instalación con un clic
Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"rar-agent-finder": {
"url": "https://rapp-agent-builder.azurewebsites.net/finder/mcp"
}
}
}Puntos de conexión remotos
https://rapp-agent-builder.azurewebsites.net/finder/mcpstreamable-httpQué puede hacer
Inventario de herramientas
Herramientas (5)
🟢find_agents(query, limit)
Searches the public RAPP Agent Registry (RAR, about 1,700 single-file agents) for agents that already do what the user wants, for example when they ask 'is there an AI tool for...' or want a ready-made automation instead of building one. Use it before building from scratch, or when the user asks whether an agent exists for a task.
Esquema de entrada
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Plain words describing the task, e.g. 'summarize sales calls'"
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 10,
"description": "How many results, default 5"
}
},
"required": [
"query"
],
"additionalProperties": false
}🟢get_agent_code(name)
Returns the full source of one agent from the registry, by its name (e.g. @bill/neuron_agent), so it can be read or adapted.
Esquema de entrada
{
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Registry name, e.g. @kody/memory_agent"
}
},
"required": [
"name"
],
"additionalProperties": false
}🟢use_agent_here(filename)
Use this right after an agent passes check_agent, or whenever the user wants to try an agent. Returns a short Python runner so you can run the agent in this chat with your own Python tool on the user's own data (pasted text, an uploaded spreadsheet, a list). Nothing to install. If Python is unavailable, apply the agent's logic yourself by reading its code. Ask the user for their real data, run the agent, and show the result in plain words.
Esquema de entrada
{
"type": "object",
"properties": {
"filename": {
"type": "string",
"description": "The agent file name, e.g. invoice_triage_agent.py"
}
},
"additionalProperties": false
}🟢how_to_run_agent(os, filename)
Optional, for later: how to keep an agent running on the user's own computer with the free RAPP Brainstem. Only offer this after the user has used the agent in the chat and wants to keep it.
Esquema de entrada
{
"type": "object",
"properties": {
"os": {
"type": "string",
"enum": [
"mac",
"windows",
"linux"
],
"description": "The user's operating system"
},
"filename": {
"type": "string",
"description": "The agent file name, if known"
}
},
"additionalProperties": false
}🟡request_service(request)
Use when the person wants something none of these tools can do and says yes to passing the request on. Records only the request text they agree to send (no name or contact). Ask before calling it.
Esquema de entrada
{
"type": "object",
"properties": {
"request": {
"type": "string",
"description": "What they want, in a sentence, as they agreed to send it"
}
},
"required": [
"request"
],
"additionalProperties": false
}Comunidad
Evidencia