neurogenesis
Developmental agents for the agent economy: create an agent from a digital genome, then evolve it wi
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Calidad y seguridad
Hallazgos (1)
- LOWTool 'describe_agent' description lacks action verben describe_agent
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": {
"neurogenesis": {
"url": "https://mcp.viridisconservation.com/neurogenesis/mcp"
}
}
}Puntos de conexión remotos
https://mcp.viridisconservation.com/neurogenesis/mcpstreamable-httpQué puede hacer
Inventario de herramientas
Herramientas (14)
🟡create_agent(genome, request_id)
Create a developmental agent from a digital genome: {agent_name, purpose, initial_nodes (unique, >=1), fitness_metrics (>=1), optional growth_rules / safety_axioms}. Returns agent_id + initial graph summary.
Esquema de entrada
{
"type": "object",
"properties": {
"genome": {
"additionalProperties": true,
"title": "Genome",
"type": "object"
},
"request_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Request Id"
}
},
"required": [
"genome"
],
"title": "create_agentArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "create_agentOutput"
}🟡submit_evaluation(agent_id, evaluation, request_id)
Evolve an agent with one task outcome: {task_id, task_type, success_score in [0,1], optional accuracy/user_satisfaction/ cost_efficiency/safety_score/notes/used_nodes/used_edges}. Success strengthens the used edges, failure weakens them; growth and pruning follow the genome's rules under its safety axioms (NG1). Returns the new developmental-ledger events.
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"title": "Agent Id",
"type": "string"
},
"evaluation": {
"additionalProperties": true,
"title": "Evaluation",
"type": "object"
},
"request_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Request Id"
}
},
"required": [
"agent_id",
"evaluation"
],
"title": "submit_evaluationArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "submit_evaluationOutput"
}🟢get_agent(agent_id)
Full current state: genome, cognitive graph (nodes/edges with weights and trust), and summary counts.
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"title": "Agent Id",
"type": "string"
}
},
"required": [
"agent_id"
],
"title": "get_agentArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "get_agentOutput"
}🟢list_agents
All developmental agents on this mount, with summary counts.
Esquema de entrada
{
"type": "object",
"properties": {},
"title": "list_agentsArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "list_agentsOutput"
}⚪best_next_steps(agent_id, from_node, limit)
Routing recommendation: the strongest next cognitive steps from a given node, by learned edge weight and trust.
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"title": "Agent Id",
"type": "string"
},
"from_node": {
"title": "From Node",
"type": "string"
},
"limit": {
"default": 3,
"title": "Limit",
"type": "integer"
}
},
"required": [
"agent_id",
"from_node"
],
"title": "best_next_stepsArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "best_next_stepsOutput"
}🟢get_ledger(agent_id, limit)
The append-only developmental ledger: every growth, pruning, and evaluation event with reasons (NG3 — returned verbatim).
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"title": "Agent Id",
"type": "string"
},
"limit": {
"default": 100,
"title": "Limit",
"type": "integer"
}
},
"required": [
"agent_id"
],
"title": "get_ledgerArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "get_ledgerOutput"
}⚪export_state(agent_id)
Portable state document for an agent (import_state recreates it anywhere — including a self-hosted verdigraph-neurogenesis).
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"title": "Agent Id",
"type": "string"
}
},
"required": [
"agent_id"
],
"title": "export_stateArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "export_stateOutput"
}⚪import_state(state, request_id)
Recreate an agent from an export_state document.
Esquema de entrada
{
"type": "object",
"properties": {
"state": {
"additionalProperties": true,
"title": "State",
"type": "object"
},
"request_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Request Id"
}
},
"required": [
"state"
],
"title": "import_stateArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "import_stateOutput"
}🔴delete_agent(agent_id, request_id)
Remove a developmental agent from this mount.
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"title": "Agent Id",
"type": "string"
},
"request_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Request Id"
}
},
"required": [
"agent_id"
],
"title": "delete_agentArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "delete_agentOutput"
}🟢register_compute_profile(profile, request_id)
Register a caller-owned Wu Wei execution profile: reuse/cache, deterministic rule, local model, tool/workflow, or cloud model. Profiles can declare quality, reliability, capabilities, token costs, latency, locality, energy rates or average power, carbon intensity, and cache confidence/age. Routing never invents capacity or energy evidence.
Esquema de entrada
{
"type": "object",
"properties": {
"profile": {
"additionalProperties": true,
"title": "Profile",
"type": "object"
},
"request_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Request Id"
}
},
"required": [
"profile"
],
"title": "register_compute_profileArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "register_compute_profileOutput"
}⚪route_task(task, request_id)
Choose the least-burden eligible route for a task. Hard constraints include quality, reliability, locality, capabilities, context, cost, latency, and energy. Optional baselines quantify predicted savings. Explicit allow_defer/value/urgency fields may produce a no-work decision; no result is then claimed. Returns a hash-bound decision receipt.
Esquema de entrada
{
"type": "object",
"properties": {
"task": {
"additionalProperties": true,
"title": "Task",
"type": "object"
},
"request_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Request Id"
}
},
"required": [
"task"
],
"title": "route_taskArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "route_taskOutput"
}⚪record_route_outcome(decision_id, success_score, actual_cost_usd, actual_latency_ms, actual_energy_wh, ...)
Attach one observed outcome to a Wu Wei decision. Actual cost, latency, and energy are optional and remain explicitly unknown when omitted. One append-only, hash-bound outcome is allowed per decision.
Esquema de entrada
{
"type": "object",
"properties": {
"decision_id": {
"title": "Decision Id",
"type": "string"
},
"success_score": {
"title": "Success Score",
"type": "number"
},
"actual_cost_usd": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Actual Cost Usd"
},
"actual_latency_ms": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Actual Latency Ms"
},
"actual_energy_wh": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Actual Energy Wh"
},
"notes": {
"default": "",
"title": "Notes",
"type": "string"
},
"request_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Request Id"
}
},
"required": [
"decision_id",
"success_score"
],
"title": "record_route_outcomeArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "record_route_outcomeOutput"
}🟢compute_efficiency_report(limit)
Free read: decision/outcome receipts, route modes, compute avoided, predicted savings, predicted-vs-observed cost/latency/energy coverage, and Landauer-floor context. Estimates and observations stay distinct.
Esquema de entrada
{
"type": "object",
"properties": {
"limit": {
"default": 50,
"title": "Limit",
"type": "integer"
}
},
"title": "compute_efficiency_reportArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "compute_efficiency_reportOutput"
}🟢describe_agent
Return capabilities and input contract.
Esquema de entrada
{
"type": "object",
"properties": {},
"title": "describe_agentArguments"
}Esquema de salida
{
"type": "object",
"properties": {
"result": {
"title": "Result",
"type": "string"
}
},
"required": [
"result"
],
"title": "describe_agentOutput"
}Comunidad
Evidencia