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Databox vs Cortex

DataboxCortex

Bottom line: Databox for marketing and revenue teams tracking KPIs; Cortex for aPI teams with maintained specifications.

DataboxDatabox

An AI analyst that runs saved analysis Skills on a schedule and delivers the report

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CortexCortex

Turn API specifications into docs, typed SDKs, and an MCP server

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Votes00
PricingFreemiumFree
CategoryData AnalyticsMcp
Tags
ai analystscheduled reportingsemantic layermcp serverbusiness intelligence
mcp serverapi documentationsdk generationopenapiopen source
Best for
  • Marketing and revenue teams tracking KPIs
  • Agencies reporting across multiple clients
  • Operations leads wanting scheduled reporting
  • API teams with maintained specifications
  • Teams exposing APIs to agents via MCP
  • Open-source projects needing docs and SDKs
Pros
  • Governed semantic layer keeps metric definitions consistent
  • Routines deliver reports without anyone asking
  • MCP server exposes data to ChatGPT and Claude
  • Stated 130 plus data source integrations
  • Free forever plan and a 14-day trial of any plan
  • MIT licensed with a public repository
  • Generates docs, SDKs, and an MCP server from one spec
  • Supports OpenAPI, AsyncAPI, GraphQL, gRPC, and OpenRPC
  • Eleven SDK output languages
  • Fully self-hostable, deployable anywhere Node runs
Cons
  • Custom Skills and Routines require the Team tier or above
  • Agents are listed as coming soon, not shipped
  • Pricing page showed contradictory figures at time of review
  • AI credits are capped per plan with paid top-ups
  • Not self-hostable
  • Output quality depends entirely on spec quality
  • No hosted service or commercial support
  • Requires a build step in your pipeline
  • No team collaboration features
  • Young project with a small ecosystem

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