Orphex MCP - Run your entire digital marketing stack via one unified MCP

@kubra_yar Thank you! Yes. Because Orphex pulls every platform into one context, you can ask “Which campaigns are underperforming across Meta, Google and TikTok etc this month, and where should budget move?” and get one ranked answer on a common basis (spend, conversions, CPA, ROAS), instead of comparing four dashboards. Orphex also flags issues it detects in your accounts on its own, and its built-in guides help diagnose why something underperforms: a real performance drop, creative fatigue, a pacing problem, or a tracking or attribution change.

From there, it can propose the reallocation itself: lower budget here, raise it there. Each change is previewed against your guardrails and only applied once you approve it. Afterwards, Impact Analysis can measure whether the shift actually drove incremental results.

@hakan_cadirci Thanks! Yes, with one nuance. Every proposal comes back as a structured preview before anything runs: the target’s current value read live from the platform, the exact values that will be sent, the guardrail verdict, and the account and currency it applies to. The proposal itself is plain JSON in the tool call, so developers see exactly what was asked for.

The confirm token is cryptographically bound to that preview. What executes is exactly what you approved, and if anything changed in between, the confirm is refused. For some platforms the preview also includes the native request body, and where the platform supports it (Google Ads, for example), the change is validated by the platform itself before you confirm. For other platforms you see the normalized fields rather than the raw HTTP request.

There’s also a readiness check for every action: it tells you whether a call would be accepted, and why not, without creating a proposal at all.

@melike_duzduran Thank you! Yes, and that’s a core part of the design. Each brand lives in its own workspace with its own context:

• Brand memory: your team’s rules, preferences, past decisions and learnings for that brand (“never pause brand search”, “margin matters more than revenue for this client”, “we tested broad match in Q2 and it failed”). The assistant reads them before analyzing or proposing anything.

• Goals and strategy: each brand’s targets and business context, so “good” is judged against that brand’s priorities, not a generic benchmark.

• KPI scorecards: targets per brand with on-track/off-track forecasts, plus a routine that flags what’s drifting every week.

• Per-brand guardrails: spend limits and approval rules set separately for each brand.

So the question shifts from “which campaign has the best ROAS?” to “what moves this brand toward its goal, within its rules?” The agent recommends; your team still approves every change.

Thanks @emre_firtana , good question! Orphex keeps data organized by workspace, and each connected account is read independently, so numbers from different accounts aren’t blended together. If you manage multiple brands, the healthiest setup is one workspace per brand, ensuring each workspace only touches that specific brand’s data. If you have several accounts on the same platform, any change must specify its target account, and nothing is applied until you approve the preview. Are you connecting accounts for one brand or several?

@ulas_gulhan thanks! Yes. Since Orphex works through your AI assistant, you can set up a scheduled task (e.g. every morning, or every few hours on Black Friday) that checks Meta, Google Ads and TikTok, flags ROAS drops and conversion changes, and proposes where budget should shift.
Any change still arrives as a preview and only happens after approval, within the limits you set (who approves, second approver, budget caps, protected campaigns).

@fatih_eren_saribuga Great question. That’s exactly the trap Orphex is built to avoid. Its diagnosis method separates measurement from performance before anything is recommended:

1. Split the drop. Spend, conversions per spend and value per conversion, then the funnel: CTR, CPC and conversion rate. Conversions collapsing while impressions and clicks hold steady is treated as a measurement break until shown otherwise, not as an ad problem.

2. Check tracking at the source. For example, each Google conversion action’s status and when it last received data, Meta’s tracking specs on the ad, and your GTM container (paused tags, consent settings, live version vs. draft). A “tracking is broken” verdict has to rest on that evidence, never on a falling count alone.

3. Compare against the store. If the platform’s conversions fall but your Shopify orders don’t, it’s attribution or tracking. If orders fall too, while clicks and traffic still arrive, look at the site or checkout.

4. Rule out the quieter causes. A changed attribution window or conversion value setting, conversions still arriving for recent days, edits made in the platform’s own UI, or ads stuck in review.

Only when all of that is clean does it call the drop a performance issue. Even then, it starts with a read-only diagnosis; any budget or bid change goes through preview and your approval.

@oleksii_sekundant Exactly, that’s the gap we kept hitting ourselves. All advertising platforms can both “own” the same conversion, because each one counts it under its own attribution method and window. Orphex shows every platform’s number side by side, each tied to the platform that reported it, and never quietly merges them into one total. You can also switch attribution windows, for example 1-day vs 7-day click, and watch how each platform’s count shifts. When the numbers disagree, you can see exactly why. Thanks for calling it out!