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io.github.jdhart81/neurogenesis

io.github.jdhart81/neurogenesis · v0.2.0

Measured by MCP Station

Description written by the publisher, not verified

Developmental agents for the agent economy: create an agent from a digital genome, then evolve it wi

Connect

claude mcp add --transport http neurogenesis https://mcp.viridisconservation.com/neurogenesis/mcp

{
  "mcpServers": {
    "neurogenesis": {
      "url": "https://mcp.viridisconservation.com/neurogenesis/mcp"
    }
  }
}

Tools as reported by the server

• create_agent
  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.
• submit_evaluation
  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
• get_agent
  Full current state: genome, cognitive graph (nodes/edges with weights and trust), and summary counts.
• list_agents
  All developmental agents on this mount, with summary counts.
• best_next_steps
  Routing recommendation: the strongest next cognitive steps from a given node, by learned edge weight and trust.
• get_ledger
  The append-only developmental ledger: every growth, pruning, and evaluation event with reasons (NG3 — returned verbatim).
• export_state
  Portable state document for an agent (import_state recreates it anywhere — including a self-hosted verdigraph-neurogenesis).
• import_state
  Recreate an agent from an export_state document.
• delete_agent
  Remove a developmental agent from this mount.
• register_compute_profile
  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 n
• route_task
  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 cla
• record_route_outcome
  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.
• compute_efficiency_report
  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.
• describe_agent
  Return capabilities and input contract.

Repository · JSON · Text for agents · Registry updated 2026-09-02