SpamZilla does not currently provide an official public MCP server, connection endpoint, OAuth flow, or customer API. If you want ChatGPT, Claude, or an AI agent to search and organize expired domains, use a supported MCP interface instead of putting a scraper between the assistant and your account.
Table of Contents
- Table of Contents
- Does SpamZilla have an MCP server?
- Why the missing API matters
- Could someone build a third-party SpamZilla MCP anyway?
- What people usually mean when they ask for SpamZilla MCP
- A supported workflow with Karma.Domains MCP
- SpamZilla MCP vs. Karma.Domains MCP
- Three ways teams use this in practice
- Where the MCP workflow ends
- When SpamZilla still makes sense
Does SpamZilla have an MCP server?
If you searched for “SpamZilla MCP,” you probably want to do more than open another domain table. You want ChatGPT, Claude, or an agent to search expired domains, narrow the results, remember your criteria, and keep a shortlist organized while you work.
I checked SpamZilla's public website, help center, pricing page, and published integration information. I could not find an official public MCP server, a connection endpoint, an OAuth flow, or a catalog of MCP tools. SpamZilla's own API FAQ also says there is no API “at the moment.” That answer has been sitting in the help center for six years.
No public SpamZilla MCP server is available for a regular customer to connect to today. There may be private or partner integrations that are not public, but those cannot support a workflow you need to build and maintain yourself.
Why the missing API matters
MCP, or Model Context Protocol, is an open standard that lets an AI application call tools and access external data. For expired-domain research, useful tools might search a database, open a domain report, check current availability, or save a note.
The protocol does not supply the domain data. An MCP server still needs a supported way to read and update the underlying service. Usually that means a documented API with stable authentication, known fields, rate limits, and predictable error responses.
SpamZilla does not offer that public layer. Its FAQ says an API was planned, and an older SpamZilla launch thread on BlackHatWorld mentioned a partner API that was not open to customers. I found no public API documentation, endpoints, or self-service credentials.
After this much time, I would not design a production workflow around the assumption that public access is about to appear. That is my assessment of the available evidence, not an announcement from SpamZilla.
Could someone build a third-party SpamZilla MCP anyway?
A developer can make almost any website look like a tool by driving a browser or scraping pages. The result may even work during a demo. I would not put it in an agency's daily domain pipeline.
A scraper-based MCP depends on page markup, internal requests, session cookies, and whatever anti-bot checks the site introduces. A small interface change can break the workflow without a versioned API change or deprecation notice. The wrapper may also need access to your SpamZilla login, which creates a credential risk if the server is operated by someone else.
There is a more direct problem. SpamZilla's published Terms of Use prohibit automated or non-human access, systematic retrieval, data-mining tools, robots, scrapers, and unauthorized scripts. The terms also reserve the right to suspend or terminate access. A community wrapper does not turn those methods into a supported integration.
I am deliberately leaving out instructions for scraping or bypassing those controls. If an MCP connection depends on behavior the service prohibits, it is a poor foundation for client work.
What people usually mean when they ask for SpamZilla MCP
Most people are not attached to a protocol for its own sake. They are trying to remove repetitive work from domain research.
A useful expired-domains MCP should let an SEO professional:
- Find auction, backorder, buy-now, and expired domains using niche, TLD, price, timing, and SEO criteria.
- Refine the same search in conversation instead of rebuilding filters from scratch.
- Open a full report and inspect domain history, anchor text, backlinks, traffic signals, and spam risk.
- Save criteria for a client, market, or PBN project and run them again later.
- Keep the decision trail with favorites, tags, notes, and shareable reports.
- Recheck a finalist before a bid or registration.
That workflow needs state. A list of domain names in chat is only the first step. The assistant needs to know which filter belongs to which client, why a candidate was rejected, and which names still need a manual review.
A supported workflow with Karma.Domains MCP
This is the problem we built the Karma.Domains MCP server to handle. It connects the same inventory and reports used in the web app to ChatGPT, Claude, n8n, coding assistants, and other MCP clients.
The scale matters because natural-language search is only useful when the underlying inventory and filters are broad enough. Karma.Domains covers more than 13 million domains, processes 400,000+ domains each day from 40+ sources, and supports 90+ filters across many gTLDs and ccTLDs. Reports bring together available data from Ahrefs, Majestic, Moz, Semrush, Similarweb, the Wayback Machine, and other sources. The hosted server currently exposes 31 MCP tools.
ChatGPT and Claude.ai can connect through OAuth, so setup is a browser sign-in rather than a small integration project. Other clients can use the same Pro API key as the Public API.
A normal agency session might go like this.
Start with the actual brief
Try:
Find
.comauction domains for a US home-services client. Maximum current price $500, Moz DA at least 20, no hyphens, and at least three years of clean English-language history.
The assistant turns that request into structured filters and returns a shortlist with links to the filtered table and full reports. If the result is too narrow, you can change one condition without starting over:
Keep the niche and history rules, but lower the DA floor to 15 and include
.net. Show me the next ten.
Save the criteria, then keep the reasoning
Once the search behaves the way you want, save it under the client or project name. The MCP can list saved filters and run them again, which is useful when new domains enter the database.
Save these criteria as
acme-home-servicesso I can apply the same filter during next Monday's review.
The MCP server itself does not schedule a future run. The saved filter preserves the search logic; a scheduled agent or workflow tool can trigger it later. In a regular ChatGPT or Claude session, you simply ask to run the saved filter when you return.
When a domain deserves a second look, the assistant can add it to favorites, apply a tag, and write a note on the report.
Tag
ridgeviewheating.comasclient-acmeandshortlist. Add a note that the Wayback history looks relevant, but the commercial anchors need a manual check.
That small note matters a week later. It also keeps another team member from repeating the same first-pass review.
Verify finalists before money changes hands
A domain report is a snapshot. Auction status, registration availability, and some external metrics can change. The MCP includes live checks for expiry and availability, Domain Authority, backlinks, anchor text, traffic, WHOIS, DNS, and other signals.
Check the current availability and expiry status of the three finalists. Then create guest share links for the two that still pass.
SEO Enrich belongs at the end of this flow, and only when a report is missing the SEO data you need. Most Karma.Domains reports already contain the available metrics. If a finalist has a gap, the assistant can start an enrich job and check its status.
This report is missing current SEO metrics. Run SEO Enrich for this finalist and tell me when the job finishes.
Using enrich on every candidate would waste credits and slow down a process that should get cheaper as the list gets shorter.
SpamZilla MCP vs. Karma.Domains MCP
The table below compares the supported MCP workflow, not every feature in the two web dashboards.
| Workflow capability | SpamZilla | Karma.Domains MCP |
|---|---|---|
| Official public MCP server | None found on the public site | Hosted official server |
| Connection and authentication | No public MCP endpoint or OAuth flow | OAuth for ChatGPT and Claude.ai; Pro API key for other clients |
| Public API foundation | No documented public customer API | Public API and MCP use the same Pro key |
| Natural-language inventory search | No supported MCP workflow | Search through ChatGPT, Claude, and other MCP clients |
| Saved filters in MCP | No official MCP tool catalog | List, save, and reuse filters |
| Notes, tags, and favorites in MCP | No official MCP tool catalog | Read and update the working shortlist |
| Guest share links in MCP | No official MCP tool catalog | Create a client-friendly report link |
| Live checks in MCP | No official MCP tool catalog | Availability, expiry, DA, backlinks, anchors, traffic, WHOIS, DNS, and more |
| SEO Enrich in MCP | No official MCP tool catalog | Run on demand when a report lacks needed SEO data |
| Supported automated access | Published terms restrict automated and scraper access | Official hosted interface with documented limits |
Three ways teams use this in practice
An SEO agency can save one filter per client and reuse the same screening logic as new inventory arrives. Notes and tags preserve the reason behind each decision, while guest links make handoff easier for an account manager or client.
A PBN or affiliate team can search by niche, language, geography, link metrics, and historical risk. The MCP handles the broad first pass. A specialist then reviews a small set of candidates in detail before bidding.
A solo SEO can use ChatGPT or Claude as the first reviewer instead of spending an evening switching between filters and tabs. The final judgment still belongs to the specialist, but the mechanical part of the shortlist takes far less attention.
Where the MCP workflow ends
MCP gives an assistant tools. It does not make every chat autonomous, and it should not make the final purchasing decision for you.
For scheduled monitoring, connect the MCP server to n8n, OpenClaw, Hermes, or another agent that can run on a timer. That setup can apply a saved filter, tag new matches, and send a digest. I would still require human approval before a bid or registration.
I also keep the expensive deep checks until the shortlist is small. Ahrefs, Semrush, and DataForSEO are useful for a final backlink audit, competitor context, or fresh SERP data. Running those checks across thousands of raw candidates is usually an expensive way to rediscover that most domains were never worth reviewing.
When SpamZilla still makes sense
SpamZilla remains a useful manual research product for people who like its dashboard, automated spam checking, domain data, and 70+ filters. Its Standard plan is listed at $37 per month. If your process stays inside the browser and the SpamZilla scoring system fits your method, the absence of MCP may not matter.
The gap appears when the assistant needs supported access to the data and needs to take structured actions. Without a public MCP server or public API, SpamZilla cannot be the direct tool layer for ChatGPT, Claude, or an agent. A scraper adds fragility and account risk instead of solving that design problem.
For conversational domain research, I would use an official expired-domains MCP with documented authentication and tool behavior. Karma.Domains lets the assistant search, reopen saved criteria, annotate reports, run live checks, and hand a small, documented shortlist to the person who will make the purchase.
The Karma.Domains MCP setup page has the current endpoint, authentication options, tool list, limits, and connection steps for supported clients.