[!TIP] The interesting part is not that it finds evidence. It is that you can check it. Every id in every answer resolves through GET /v1/evidence/{id}, and POST /v1/verify will re-resolve a set of claims against the corpus, ours or anybody else's. An id that does not resolve is a claim that was never real.

{
  "finding": "Sizing runs small, and buyers only discover it after delivery",
  "corroboration": { "records": 31, "channels": 5 },
  "receipts": ["rc_8f2a1", "rc_44b0e", "rc_91c37"],
  "confidence": "finding"
}

GET /v1/evidence/rc_8f2a1 returns the actual comment, its score, where it was posted, when, and its permalink. A customer of your customer can click a claim and read the human who said it.

The hosted API lives at https://quorum-api-j15n.onrender.com, on a free tier instance that sleeps when idle, so the first request after a quiet spell waits a few seconds for it to wake.

The hosted instance is keyed while the API is early. The API root says how to request a key, and always says which mode the instance you are talking to is in. The health endpoint needs no key, so you can check it is alive right now:

curl https://quorum-api-j15n.onrender.com/v1/healthz

Self hosting supports open mode or per key auth, quotas, tenancy and webhook secrets, all self served from GET /v1/usage.

[!NOTE] On Windows, the curl bundled with Git Bash uses the Schannel TLS stack, which refuses any HTTPS connection when it cannot reach the certificate revocation servers (CRYPT_E_REVOCATION_OFFLINE, common behind corporate proxies and VPNs). That is the network, not this API. Add --ssl-revoke-best-effort to the curl command, or call from WSL or PowerShell instead.

Contents

• What it does
• Use cases
• Status
• Requirements
• Quick start
• Usage
  • CLI
  • HTTP API
  • JavaScript SDK
  • Python SDK
  • MCP server
  • Webhooks
  • Running the API yourself
  • Postgres
• What the API does
• Why this is different
• Documentation
• Contributing
• License
• Acknowledgements

What it does

Voice of customer from public archives, competitor ads ranked by how long they have actually been running, and a video versus static verdict computed as arithmetic rather than opinion. It keeps everything it reads, so the second question about a market is nearly free and the archive can be asked about the past.

Key capabilities

• Receipts, not links. A stable id into a retained corpus, which resolves identically forever, including after the source deletes the original.
• Corroboration as arithmetic. A claim needs at least three independent records before it prints as a finding, and the count travels with it.
• Ten sources behind one interface, from a volunteer Reddit archive and GitHub issue search to four government safety regulators, each degrading rather than failing when unconfigured.
• A corpus that compounds. Cold retrieval measured 596 seconds and about 500 throttled requests. The same category answers in half a second once warm.
• Offline mode that touches no network and costs nothing.
• Fifteen HTTP operations, a typed SDK, an MCP server and a CLI, all the same pipeline.

What it looks like

Real output, excerpted from a cold npx quorum "espresso machine" run on 2026-08-24: 401 records in 227 seconds for $0.00.

EVIDENCE  a claim needs 3 independent receipts to be stated as a finding
          the percentage is share of all 401 records held for this category

  quality     88 receipts /  64 channels  21.9%  A0 B3 C85 D0   [finding]
      "I often hear the priority list being 1. Quality of beans 2. Quality
       of the grinder 3. Quality of the espresso machine..."
         hackernews Why a spritz of water before grinding coffee yields
         better results   rc_4d6d444821b0044f

ATTESTED  7 records from 6 named parties   [finding]
  A named party stated this to a regulator, on the record, with consequences
  for lying. Two of these are a finding on their own.

      "CPSC And Krups Announce Action On Espresso Makers..."
         cpsc Krups   rc_a4883bfb1b04d1c1

RECEIPTS  195 cited, 195 resolved back to real records

COST      $0.0000 in 227.3s

Every id in that output is fetchable from the corpus that run wrote. If an id does not resolve, the run exits non zero and says which one.

Use cases

• Product and brand research. What buyers actually complain about, with the comment behind every claim, rather than a summary you have to trust.
• Competitive teardown. One full retrieval per rival, so shares are compared instead of counts, and co-occurrence is never mistaken for a signal.
• Ad creative decisions. Video versus static judged by how long real campaigns ran, from dated observations rather than from a platform's own label.
• Agent tooling that can be audited. An MCP server whose every claim the calling model can independently resolve, which is the one thing a research tool cannot fake.
• Diligence and monitoring. Attested records a named party filed with a regulator, and a diff against the last report for the same subject.

Status

[!NOTE] Do not depend on the API shape yet. It is stable enough to build against and not yet frozen.

Named rather than left as a surprise: request quotas are held in memory, so the per minute lookup counter resets on restart and none of the counters would hold across two instances. The hourly report counter is the exception: it is re-seeded from persisted reports at boot, so a restart is not a refill. And evals/ holds only its first layer, a labelled relevance set scored in CI; the paid, scored report evals described in the project docs do not exist yet.

Requirements

Node 22.18 or newer. The engine has one runtime dependency, pg, and only in the hosted server: no framework, no ORM, no HTTP client, no test runner, and nothing at all in the CLI or the corpus. That is a deliberate constraint rather than a boast, because every dependency in a tool that fetches untrusted text from the public internet is another thing that can reach the network on your behalf. pg earned its place by being a connection pool that survives a database restart, which is not a thing worth hand writing.

No key is required for anything. Reddit through a public archive, Hacker News, the App Store and four government safety archives are all free and keyless. Keys only ever ADD sources, and a missing one degrades a run rather than failing it.

Read the full README on GitHub →