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What is Occam?

Your AI is good at reasoning. It is bad at silently inventing what a web page said.

Occam is a locally run host that sits between your AI and the public web. It acquires real page content, shapes it for a model’s context window, returns a typed refusal when the content is unknown, and can optionally attach integrity artifacts you can verify later against a key.

Your AI
   |
   | MCP / CLI
   v
 Occam (local host)
   |
   +-- acquires the page (HTTP → browser → optional managed)
   +-- materializes token-budgeted Markdown / structured fields
   +-- returns ok:false when content is UNKNOWN
   +-- optionally signs what it produced (integrity vs a key)

The problem

Without a dedicated extract layer, agents either:

  • skip the fetch and hallucinate from training memory, or
  • dump raw HTML into the context window and waste tokens

Neither is trustworthy for research, citations, or automation.

What happens on a normal read

  1. The AI asks Occam to read a URL (usually occam_transcode with only url).
  2. Occam acquires the page now through a gated ladder (HTTP first; browser when the HTTP result is unusable; optional managed provider only after both local attempts fail).
  3. Usable content is materialized: budgeted, optionally focused, optionally structured.
  4. On success: ok: true plus Markdown (and optional structured sidecars). A signed receipt may be attached.
  5. On failure: ok: false with a typed failure.code — content is unknown, not guessed.

Live extraction is the default. An opt-in response cache (cache_ttl_s) can replay a prior materialization on the same machine — it is not a CDN, and it is off unless you set it.

Beyond one URL

Occam also supports:

  • Discovery before a full read — probe, map, search
  • Several URLs in one call — digest
  • Site recipes (playbooks) — resolve, heal, lint, save
  • Typed fields — extract_knowledge (needs a schema)
  • Evidence lookup / citation assessment — claim_check, attest (heuristic — not truth proof)
  • Integrity checks — receipts, verify, dataset export
  • Experimental opt-ins — watch, crosscheck, batch, failure atlas

What it does not promise

Not this Reality
Proves the page was true Signatures prove integrity relative to a key
Proves origin authenticity / identity Local self-minted key; no PKI / registry
Trusted timestamps Signer clock only (optional TSA is separate and limited)
CAPTCHA solving Detects walls; does not bypass them
Universal npm install npm is not a GA 1.0 channel (experimental RC packages ff-occam / @ff-occam/mcp exist)
Cosign as page-content truth Published v1.0.0-rc.3+ use signaturePolicy=required-cosign-v1 (SHA-256 always + Cosign fail-closed). Cosign proves release authenticity vs the workflow identity — not page truth. v1.0.0-rc.2 remains SHA-256-only
Marketplace “trusted auto-merge” Community automation is operational machinery, not a trust guarantee

Who it is for

You Occam helps you
Person using Cursor / Claude / Codex / Hermes One install, then ask the agent to read the web
Operator Local install, connect, doctor, sessions, packaging
LLM agent Typed tools, honest failures, compact llms.txt map
Auditor Verify receipts offline without trusting the chat transcript

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