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29 days ago
glama

ExD Accelerator MCP Server

AI-native Experience Decisioning lifecycle automation for Adobe Journey Optimizer. End-to-end ExD setup from a single chat conversation: CSV → schema fields → offers → collections → eligibility rules → ranking → selection strategy → placements.

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// key findings
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
🔐
You'll be asked for 1 credential: CLIENT_SECRET
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// required environment variables
This server reads these from process.env. You'll be asked to provide them before it can run.
configCLIENT_IDcp .env.example .env # fill in , CLIENT_SECRET, sandbox, schema, catalog
🔐 secretCLIENT_SECRETcp .env.example .env # fill in CLIENT_ID, , sandbox, schema, catalog
configDECISIONING_SCHEMA_ALT_ID"": "_….schemas.…",
configDECISIONING_SCHEMA_URI"": "https://ns.adobe.com/…/schemas/…",
configITEM_CATALOG_ID"": "xcore:decision-catalog:…"
configORG_ID"": "…@AdobeOrg",
configPORT
configSANDBOX_NAME"": "…",
configTENANT_ID"": "…",
// full audit trail
The full breakdown of what we checked, the deductions that landed, the network hosts, the dependency advisories, and concrete fix guidance is available to verified publishers.
// improvement guidance — verified publishers only
We have 3 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[![M8ven Score](https://m8ven.ai/badge/mcp/khushi-nayal-decisioning-mcp-k9fnid)](https://m8ven.ai/mcp/khushi-nayal-decisioning-mcp-k9fnid)
commit: d861dab11637de1e90d389c6c052bd2b821acdb2
code hash: 14bd5ef5bb81e790de7c8407eb8fd45729a8541f43570ce4618fd93055622568
verified: 7/2/2026, 9:17:14 AM
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