Marketo’s API gives you 50,000 calls per day on a standard subscription, at a rate of 100 calls every 20 seconds. Run it at full throttle and the entire daily budget is gone in under three hours. Then every integration, every workflow, and every agent your team runs sits idle until the clock resets.
These limits are published in Adobe’s own docs. They were tolerable when the only API consumer was a nightly CRM sync. They are fatal now that the fastest-growing consumer of your marketing data is an AI agent.
Ask around about why enterprises are struggling to accelerate with AI and you’ll hear plenty of theories: the models aren’t ready, the use cases aren’t clear, the org isn’t bought in. Our bet is on something more boring. Your business context is scattered across a dozen systems of record, and the tools holding that data were never designed to give it back. We call this the data accessibility thesis, and it shapes how we build everything at Conversion.
Lock-in was the point
For the platforms of the past, data accessibility was never a priority. It was the opposite. Holding your data hostage was the moat: the harder it was to pull your contacts, campaign history, and engagement data out, the harder it was to leave.
So legacy vendors built their API infrastructure with serious throughput and availability constraints baked into the core. Fifteen-plus years later, those constraints are effectively permanent. You cannot retrofit high-throughput, real-time access onto an architecture that assumed the only consumer was an occasional nightly integration. The result is a vault with a mail slot. Your data is technically in there. You can technically get it out, one envelope at a time.
This matters more than ever because the new AI features these vendors are shipping, including their MCP servers, sit on top of the same pipes. Bolting an agent interface onto a constrained API doesn’t remove the constraints. It gives the agent a front-row seat to them.
Agents changed what “access” means
LLMs are now smart enough to automate a large share of your marketing operations. But intelligence without your business context is worthless. An agent that can’t see your pipeline, your product usage, or your campaign history is a very smart intern on their first day, forever.
That’s why teams are wiring more systems together than ever before: CRM, warehouse, support, billing, product events. Every connection makes their agents smarter. In this era, a system’s value comes as much from what it exposes as from what it does.
Every tool in your stack now serves two audiences: the humans who click around in it, and the agents that read from it and act through it. The second audience is growing faster than the first, and it doesn’t tolerate friction. Rate limits sized for a 2010-era server. Metered API tiers that turn your own data into a line item. Daily extract caps that make the warehouse wait. These were annoyances for humans. For agents, they’re a wall.
The systems that win the next decade will treat programmatic access as a first-class product. That means a free and open API. It means a proper MCP server, so any agent your team runs can query, reason, and act with full context and correct permissions. It means your data leaves as easily as it arrives.
Our thesis: no black box, no walled garden
The bet we’re making at Conversion: to power the agentic future, data must move as freely as possible between your systems of record.
The platforms of the past used data as a moat. We believe the best platform of the future will win on merit. If your product is only sticky because leaving is painful, you’ve stopped competing. We’d rather make our data so accessible that customers could leave any time, and build a product good enough that they never want to.
In practice, the difference looks like this.
Marketo vs. Conversion, by the numbers
Marketo’s limits, straight from Adobe’s docs:
- Max 50,000 API calls per day on a standard subscription
- 100 calls per 20 seconds (5 requests per second), with a concurrency limit of 10
- No real-time segmentation or searching through contacts
- Hard caps on custom fields: 100 for leads, 20 for program members, and 50 for custom objects
And Marketo’s MCP inherits many of the same limitations, because the agent interface is new but the pipes underneath are fifteen years old.
Conversion:
- No daily cap, with a rate limit of 200 requests per second
- Batch updates to contacts, audiences, and campaigns at up to 1,000 records per call
- No limits on custom fields
- A first-class MCP server and an open API
The gap comes down to philosophy. One architecture was designed to meter access to your data. The other was designed to hand it over as fast as you can ask for it.
What an open MCP unlocks
So what do you do with all that headroom? This is where it gets fun. An open MCP on a strong API foundation unlocks a class of agents that can’t exist behind legacy rate limits:
Unconstrained background agents. Agents that create audiences, email campaigns, webinars, events, and workflows on schedules or triggers. Spin up dozens without watching a call budget, and let high-effort reasoning agents chew on your toughest tasks with full context.
A Slack bot that knows your MAP. Ask it anything about your marketing automation platform and it queries and segments live contact data to answer. No pre-built dashboard required.
A QA agent on patrol. One that continuously scans workflow and sync logs to surface errors before your team, or worse, your VP, finds them.
Instant reports from your AI client. Generate a report directly from Claude or ChatGPT, pulling live data through MCP, formatted however you asked for it.
None of these are moonshots. They’re afternoon builds once the data layer stops fighting you.
Demand better pipes
The last era of software competed on how well it could trap your data. The next era will compete on how well it can serve it, to your team and to the agents working alongside them. Data fragmentation is the biggest thing holding enterprises back from accelerating with AI, and the fix starts with demanding open access from every system of record in your stack.
If a vendor’s answer to “how do I get my data out” involves a rate limit and a pricing tier, you already know how their AI story ends.