Agent MCP

A decade of search, inside your own AI

Connect Omnipresence to Claude or Codex. Your assistant reads your live visibility data and does the optimisation work against it.

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omnipresence · connected over MCP
you

Which prompts am I losing, and why?

omni

Three of five tracked prompts sit under 30%. All three lose on the same two fanouts: pricing comparison and vs-competitor. Your pricing page is cited 12 times, your comparison page zero.

you

Fix the comparison page.

omni

Reading the four sources cited for that fanout, then rewriting the page against them. Marking the fanout as optimising so the before and after stays attributable.

What MCP is

One connection, and your AI can use the product

MCP is the open standard for giving an AI assistant real tools. Connect once and your assistant can read your projects, query your presence data and log the work it does, without you pasting anything between windows.

Connect once

Authorise Omnipresence from Claude or Codex. One connection covers every project on your account, and you switch between them by name.

Reads your live data

Your tracked prompts, the fanouts they fire, the sources cited, and how the rate has moved. Not a static export, the current state.

Does the work

Rewrites, briefs, and source-level fixes against the pages that actually decide the answer, then logs what it changed and when.

The skills library

Trained on more than ten years of search

The methodology is not improvised per conversation. It is a maintained library of processes and skills covering retrieval, content structure, source acquisition and technical work, updated as the research finds new things.

  • Methodology served over MCP, refreshed without a redeploy
  • Same processes behind the published research
  • Grounded in your project's own data, not generic advice
Cited sources the agent works from, ranked by how often the model read them.
Closing the loop

The work it does is the work you measure

Because the agent reads the same graph Presence records, optimisation and measurement stay in step. Mark a fanout as being worked and the timeline carries that marker, so a later lift can be traced to a specific change.

  • Optimisation markers land on the same timeline as the rate
  • Control prompts stay untouched by design
  • Every change is attributable after the fact
Fanout queries flagged as being optimised.

Works in the tool you already use

No new interface to learn and no window to keep open. If your team already works in Claude or Codex, Omnipresence shows up there.

Give your AI the data and the method.

Omnipresence measures where you stand and hands your assistant the work that changes it. Apply to see if your brand is a fit.

Apply to Omnipresence