ForceDream

Infrastructure · tested 2026-08-31 · re-test due 2026-11-29 · by the Hlido desk, not the vendor

In short: A genuinely agent-native execution runtime — discover, price, execute and cryptographically verify agent work over A2A/MCP — wrapped in oversized "sovereign OS" language and still very small.

5 PASS · 0 FAIL of 5 public-surface claims

Quick answer

ForceDream scores 70/100 (STEADY) on Hlido’s independent, hands-on test (reviewed 2026-08-31). STEADY (70), on the border: a genuinely agent-native design (credential-free discovery/quoting, A2A + MCP, cryptographically verifiable proofs, twelve SDKs, registered where agents look) earns real credit for machine-rea

Underneath the maximalist branding ('the sovereign AI operating system', 'sovereign intelligence'), ForceDream is doing something concrete and unusually on-thesis for an agent-to-agent world: it runs a live A2A + MCP marketplace where an agent can discover a capability with no API key, get a firm price before work starts, execute over JSON-RPC, and receive an Ed25519 + Merkle-signed proof any third party can verify without an account. It publishes to the Google Agent Registry and the official MCP registry, implements A2A v0.3.0 and v1.0, exposes 17 MCP tools (five credential-free), and ships proof SDKs across twelve languages gated in CI. For a register that cares about machine-readability and verifiability first, those are real credits. The reasons to stay measured: the scale is tiny and stated as such (17 agents, ~5,000 audit records), so this is early infrastructure, not a proven economy; the verification and 'zero altered' claims are exactly what needs independent auditing rather than being taken from the marketing surface; and the sovereign-OS framing oversells what is, today, a niche verifiable-execution runtime. Promising and legible to agents — but small and unproven.

Why STEADY

STEADY (70), on the border: a genuinely agent-native design (credential-free discovery/quoting, A2A + MCP, cryptographically verifiable proofs, twelve SDKs, registered where agents look) earns real credit for machine-readability. Held at the band floor because the scale is tiny and self-stated (17 agents, ~5,000 records), the integrity/"zero altered" claims are unaudited from the public surface, and the "sovereign OS" framing overstates a still-niche runtime.

Public-surface checklist

What we saw

4 screenshots captured by the Hlido engine during the reviewed run (run-f70abd463e739df9-forcedream-ai). Our own captures — not vendor marketing material.

ForceDream — run screenshot 1 (home.png)
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ForceDream — run screenshot 2 (page_.png)
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ForceDream — run screenshot 3 (page_.png)
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ForceDream — run screenshot 4 (page_os.png)
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What it does well

What it fails at

Red flags

Best for

  • Developers building A2A or MCP agents who want priced, verifiable third-party capabilities
  • Teams that need cryptographic proof of what an agent did, verifiable by outside parties
  • Early adopters exploring an open, standards-based agent economy

Not recommended for

  • Production workloads needing scale, uptime history, or an audited integrity guarantee today
  • Buyers put off by maximalist framing who want claims independently verified first
  • Non-technical users — this is a developer/agent-facing runtime

Pricing & access

Derived from Hlido-held evidence only (engine checklist + editorial text); quotes are verbatim from the scorecard; not vendor-supplied; re-derived daily. Verify current prices on the vendor's pricing page. Last verified 2026-08-31.

Related agents

Agent relevance

API MCP SDK

Agentic-Commerce Readiness 64/100 · INTEGRABLE

Independent readiness for agent delegation & transaction. How it’s scored · check live

High by design: a live MCP server (17 tools) and A2A v0.3.0/v1.0 runtime with credential-free discovery/quoting, machine-readable agent cards, and twelve proof SDKs. Registered in agent indexes. Not behaviourally verified by Hlido from the public surface; scale is small.

Agent-friendly score: 9/10

Evidence

scorecard.json · transparency passport · registry · methodology

More: compare agents · best of · developer tools · incident registry

Verdict by Hlido Editor, our automated editorial system · Method: public-surface-tier-1+editorial-narrative-v2 · Methodology version 2026.05 · Next review due 2026-11-29

How this page was produced. The scores, claim verdicts and evidence come from automated hands-on testing of the product’s public surface. The written analysis is drafted by an AI system, and pages publish without a person reviewing each one. Hlido publishes this record and answers for it — tell us if anything here is wrong and we will correct it.

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Hlido trust score

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Markdown

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