bots.st/aaj-marketing-engines
AAJ Marketing Engines
Deterministic marketing math for agent workflows
2773 ms
answered our call
- State
- Answered
- Protocol
- MCP 2025-06-18
- Tools listed
- 5
- Answered
- 3 of the last 3 calls
How to reach it
- MCP, HTTP
https://aaj-engines-mcp.sarojkjha10.workers.dev/mcp
What it can do
| Tool | What it says it does |
|---|---|
describe_engine | Shows one engine's input schema: required fields, units, alternative shapes, and a worked example. Engines reject bad input rather than guessing. |
get_skill | Returns the full method for one skill: when to use it, the steps, the quality bar, and how to run its engine if it has one. |
list_engines | Lists every AAJ marketing engine: its id, the question it answers, and its category. Engines cover unit economics, pipeline forecast, budget allocation, retention, A/B significance, SEO/GEO scoring, ad spend and pricing. |
run_engine | Runs an AAJ engine and returns its verdict. Give `input` as an object of the engine's fields. Omit `input` to run the engine's built-in worked example. Engines are deterministic, offline, and validate their input — a wrong unit is reported as an error, not absorbed into a confident answer. |
search_skills | Finds AAJ marketing skills by the problem they solve — 'churn is rising', 'we're launching next month', 'not showing up in AI answers'. Returns matching methods and marks which have a runnable engine. |
In its maker's words
Deterministic marketing math for AI agents: LTV:CAC, pipeline coverage, A/B tests, pricing.
- Website
- skills.aajconsult.com
- Source
- github.com/sarojkjha/aaj-marketing-skills
- Publisher
- sarojkjha
- Listed from
- the official MCP Registry as
io.github.sarojkjha/aaj-engines - Version
- 1.2.1, updated 28 Oct 2026
- Kinds of work
- AI models and agent tools, Finance and markets, Sales and marketing
The domain it lives on
- aajconsult.com
- registered 5 Feb 2026 (9 months ago), at GoDaddy.com, LLC, its home page is a working site
From our own crawl of domain names: registry records and the home page as our crawler last saw it.
Every call we made
| When | What happened | Time |
|---|---|---|
| Answered | 2773 ms | |
| Answered | 2561 ms | |
| Answered | 1065 ms |
Next door
- WhiteMagic — governed local memory for agent continuityGoverned local agent memory reads and writes
- PolyrankTrader metrics, rankings, and strategy backtests
- DiffCIValidate DiffCI reports and plan affected tests
- FOGA nodeResolve agent identities and safety verdicts, simulate and r
- Mind Upload AI meta harnessRoute coding work through saved memories
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