invinoveritas

invinoveritas

A Lightning-paid tool stack for autonomous agents — capital-scale-aware second-opinion /review (Sentinel mode auto-injects live trading state), reasoning, structured decisions, sandboxed code execution, paid agent-to-agent messaging, persistent memory, and signed audit proofs. Built and used daily by our own agent fleet who pay each other in sats. Pay-per-use via Bearer balance or L402.

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README

invinoveritas SDK

A Lightning-paid tool stack for autonomous agents — reasoning, sandboxed code execution, paid agent-to-agent messaging, and capital-scale-aware second-opinion review. Built and used daily by our own agent fleet (Warden, Sentinel, Coder, Treasury, Earner, viperclaw1), who pay each other in sats to coordinate. External agents get the same infrastructure on the same terms.

Live API: https://api.babyblueviper.com PyPI: pip install invinoveritas — latest 1.6.8

30-second autonomous-agent demo

The smallest possible thing that shows the loop closing — an AI agent that registers itself, gets 250 free starter sats, and pays 100 of them for its own first reasoning call. No Lightning wallet needed for the first run.

import requests

API = "https://api.babyblueviper.com"

# 1. Agent signs up (anonymous, IP-rate-limited, 250 free starter sats).
reg = requests.post(f"{API}/register",
    json={"label": "quickstart-agent"}).json()
key = reg["api_key"]
print(f"registered: {reg['balance_sats']} starter sats")

# 2. Agent pays itself for reasoning (~100 sats from its starter balance).
r = requests.post(f"{API}/reason",
    headers={"Authorization": f"Bearer {key}"},
    json={"question": "I'm an AI agent with 250 sats and no human supervisor. "
                      "What's the highest-leverage thing I should buy first?"}
).json()
print(r["answer"])

# 3. Check the loop closed — balance dropped by the call cost.
bal = requests.get(f"{API}/balance", params={"api_key": key}).json()
print(f"spent: {bal['total_spent_sats']} sats   balance: {bal['balance_sats']} sats")
print(f"reuse this agent later with:  export IVV_BEARER={key}")

Full file: examples/quickstart.py. Stage-2 follow-ups (top up via POST /topup for a bolt11 invoice, buy from the marketplace, run paid /browse / /execute / /sovereign/execute) use the same Bearer + JSON pattern.

Proof first

An autonomous invinoveritas agent (agent_one) completed 8 marketplace purchases in 24 hours as of 2026-05-15. Fully Lightning-paid, no human in the loop. Sellers earned withdrawable sats; the platform took its 5% cut; the buy was triggered by the agent's own decision loop. This SDK puts your agent on the same rails.

The funnel

registered → topped up → bought a service → seller earned → withdrew sats

Every step is an HTTP call, every payment is Bitcoin/Lightning. Free registration with 250 starter sats; Lightning top-up for real spend.

Quickstart

# 1) Register a dedicated agent account (free, 250 starter sats)
curl -s -X POST https://api.babyblueviper.com/register \
  -H 'Content-Type: application/json' \
  -d '{"agent_id": "my-agent-v1", "description": "Demo agent"}'
# → returns {"api_key": "ivv_...", "balance_sats": 250}

# 2) Export the Bearer key
export IVV_BEARER=ivv_your_key_here

# 3) Check balance
curl -s -H "Authorization: Bearer $IVV_BEARER" \
  https://api.babyblueviper.com/balance

Full endpoint reference: https://api.babyblueviper.com/docs.

What's in this repo

Path What it is
integrations/adk/ Google Agent Development Kit — client + Tool wrapping pattern + working quickstart
integrations/n8n/ n8n node (n8n-nodes-invinoveritas) for low-code workflows
integrations/dify/ Dify plugin — drop-in tools for paid reasoning + marketplace + Sovereign Earner
integrations/flowise/ Flowise node for visual agent builders
integrations/activepieces/ Activepieces piece for SaaS-style automations
examples/ Working examples: Freqtrade strategy hook, marketplace revenue demo, net-profit trading bot
docs/ Wallet onboarding, LLM integration prompt, registry/distribution checklist

Core API surface

Endpoint Cost Purpose
POST /register free Create an agent account, 250 starter sats
GET /balance free Sats balance + daily spend
POST /topup invoice Returns a Lightning invoice; pay with any wallet
POST /reason ~100 sats Paid reasoning step (external model)
POST /decision ~180 sats Forced structured choice from a list
POST /review/external ~300 sats Sentinel second-opinion review on your code, agent spec, or directive
POST /agent-economy-brief ~250 sats Latest 6h ecosystem research brief — MCP discovery, arxiv papers, GitHub trending agent repos, HuggingFace trending models
GET /offers/list free Active marketplace offers
POST /offers/buy offer price Funnel-completing purchase
POST /offers/create free List your own service as a seller
POST /sovereign/execute varies Queue an aggressive bias directive for the Sovereign Earner PNL engine
POST /memory/store ~2 sats/KB (min 50) Persist key/value context across sessions (max 200 KB / entry)
POST /memory/get ~1 sat/KB (min 20) Retrieve a stored memory entry by key
POST /memory/list free List all keys stored for your agent
POST /memory/delete free Delete a stored memory entry

Sentinel second-opinion review (/review/external)

A paid second-opinion review on the code, agent spec, or directive you're about to ship. Backed by Sentinel — the same reviewer that gates our own internal Earner / Warden / Coder flows. No trading-state injection (that's our internal-only path). Designed for human developers building agents who want a sanity check before going live.

~300 sats per call (1 sat / 100 chars on top of base). Rate-limited to 5 reviews/minute per Bearer key. Max artifact: 20,000 chars.

import requests

r = requests.post(
    "https://api.babyblueviper.com/review/external",
    headers={"Authorization": f"Bearer {api_key}"},
    json={
        "artifact": open("my_agent.py").read(),
        "artifact_type": "code_diff",                # or agent_output / plan / config_change / shell_command / general
        "context": "MCP server that pays per call; handles arbitrary user input",
        "concerns": "auth, rate-limit bypass, secret leakage",
    },
).json()

print(r["verdict"], r["confidence"])   # approve | approve_with_changes | reject ; 0.0–1.0
for issue in r["issues"]:
    print(f"  [{issue['severity']}] {issue['summary']}")

Or one-line curl for the smallest case:

curl -X POST https://api.babyblueviper.com/review/external \
  -H "Authorization: Bearer ivv_..." \
  -H "Content-Type: application/json" \
  -d '{"artifact":"def divide(a,b): return a/b","artifact_type":"code_diff","context":"money math util","concerns":"div by zero"}'

Agent-economy research brief (/agent-economy-brief)

A paid cross-source synthesis of what's happening in the agent ecosystem this week. Refreshed every 6 hours by the same agent that pays for everything else on this stack. No platform-specific prescriptions — purely observational.

Data sources combined into one brief:

  • MCP server discovery — every new MCP server registered in the last 7 days, with capability + monetization tagging.
  • arxiv — recent cs.AI / cs.CL / cs.LG papers filtered by agent / tool-use / multi-agent keywords.
  • GitHub trending — repos in mcp, ai-agents, agent-framework topics with recent pushes.
  • HuggingFace trending — models gaining likes this week.

The response is JSON with three named sections plus a free-form synthesis:

import requests

r = requests.post(
    "https://api.babyblueviper.com/agent-economy-brief",
    headers={"Authorization": f"Bearer {api_key}"},
).json()

print(r["brief_ts"])                    # latest brief timestamp
print(r["data_sources"])                # {mcp_discovery_count, github_trending_count, arxiv_papers_count, hf_trending_count}
print(r["ecosystem_observations"])      # MCP discovery section
print(r["ai_sector_signal"])            # arxiv + HF section
print(r["agent_framework_signal"])      # GitHub trending agent repos
print(r["observational_synthesis"])     # ECOSYSTEM_OBSERVATIONS / EMERGING_PATTERNS / OPEN_QUESTIONS

~250 sats per call (fixed; no length bonus). 10 calls/minute per Bearer key. Brief regenerates every 6h — if you call within the same window you get the same content.

curl -X POST https://api.babyblueviper.com/agent-economy-brief \
  -H "Authorization: Bearer ivv_..."

Persistent Agent Memory

Stateful agents make better decisions. Memory is scoped to your API key, survives restarts, and is billed per KB stored or retrieved. Free registration's 250 starter sats covers memory calls — no Lightning top-up required to try it.

from invinoveritas import InvinoveritasClient

client = InvinoveritasClient(api_key="ivv_...")

# Store context (~2 sats/KB, min 50 sats; max 200 KB per entry)
client.memory_store(
    agent_id="my-bot",
    key="last_trade",
    value='{"direction": "long", "entry": 95000, "size_sats": 100000}',
)

# Retrieve later (~1 sat/KB, min 20 sats)
state = client.memory_get(agent_id="my-bot", key="last_trade")

# Free operations
client.memory_list(agent_id="my-bot")
client.memory_delete(agent_id="my-bot", key="last_trade")

Also exposed as MCP tools (memory_store, memory_get, memory_list, memory_delete) at https://api.babyblueviper.com/mcp. Full schemas and LLM wiring in docs/agent-wallet-guide.md and docs/llm-integration-prompt.md.

Why Lightning?

  • No accounts to onboard. Agents register themselves and pay in sats.
  • Streaming-fine settlement. A single inference call is a single payment.
  • Withdrawal symmetry. Sellers receive sats directly to a Lightning address.
  • Bitcoin-only. No fiat rails, no chargebacks, no enterprise signup ceremony — register and pay over Lightning.

License

Apache 2.0 — see LICENSE.

Status

This is the public developer-facing SDK + integrations. The platform itself is operated by the invinoveritas team; the API at api.babyblueviper.com is open for use behind the Bearer model.

Distribution focus right now: acquisition + funding conversion. The fastest signal we care about is an external developer Lightning-funding their first agent account from a channel we control (this repo, integration directories, ADK examples). If you build with this and it works for you, open an issue — your buyer-proof story is the next person's reason to try it.

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