Mintlify alternative built for the agents writing your code
Searching for a Mintlify alternative usually means one of two things. Mintlify is a documentation platform: it publishes prose and API references for the people who use your product, and for the AI tools they bring with them. ContextsBase is context infrastructure for the coding agents that build your product: structured features, business rules, a data model, and test cases served over MCP, with a work queue the agent pulls from and a record it writes back to. One explains what you shipped. The other tells your agents what to ship. Most teams building with Claude Code, Cursor, or Copilot end up wanting both.
Mintlify vs ContextsBase, side by side
Mintlify cells summarise mintlify.com and its documentation. Where a detail changes often, we say “check current plans” rather than guess.
| Mintlify | ContextsBase | |
|---|---|---|
| Primary content | MintlifyProse documentation written in MDX or Markdown and stored in a Git repository, plus API references generated from an OpenAPI spec and rendered with an interactive API playground. | ContextsBaseStructured features (F-n) with functionality, business rules, and edge cases; entities with fields and foreign keys; flows as decision trees; and plain-English Given/When/Then test cases (T-n). |
| Who reads it | MintlifyYour customers and the AI tools they use. Mintlify generates an MCP server, llms.txt, llms-full.txt, and .md endpoints so agents such as Claude, Cursor, and ChatGPT can search and fetch your public docs. | ContextsBaseYour own coding agents: Claude Code, Cursor, GitHub Copilot, Windsurf, or any MCP client. Humans write specs in the app and publish them. Agents only read published features. |
| Direction | MintlifyRead-only for visiting agents. The generated MCP server exposes search and filesystem tools annotated read-only, plus a feedback tool that reports an incorrect or outdated page back to your team. | ContextsBaseRead and write back. Agents call get_feature_spec to read, then record_feature_implementation and record_test_automation to report what they built and tested. |
| Work queue | MintlifyNo queue for coding agents. Mintlify’s own writing agent proposes documentation changes as pull requests or direct commits from prompts, pull requests, or Slack threads (Pro and Enterprise plans). | ContextsBaseIterations (I-n): ordered lists of features. An agent calls next_iteration_item to claim the next one atomically, so two agents never pick up the same feature. |
| Test generation | MintlifyNot part of the product. Documentation describes behaviour; it does not hold test cases or record test results. | ContextsBaseTest cases assert business rules in plain English. Agents turn them into Playwright tests and record pass or fail against the case they came from. |
| Drift detection | MintlifyTwo signals: the writing agent can propose doc updates from connected repositories, and visiting agents can flag an outdated page through the feedback tool. There is no link between a doc page and shipped code. | ContextsBaseEvery implementation record carries a fingerprint of the spec it was built from. Edit the spec and the record turns Outdated. Reject the work and it turns Reopened. |
| Pricing | MintlifyFree first month of credits, no card required. Starter (5 editor seats), Pro (unlimited seats, agent, assistant, automations), Enterprise (contact sales). AI features are billed in credits. Check current plans for prices. | ContextsBaseFree: 1 project, 100 features, 3 members, 1 MCP token, unlimited open iterations. Premium at $5 per month is coming soon with unlimited projects, features, and members. |
Mintlify is a trademark of its owner. ContextsBase is not affiliated with Mintlify. Details checked September 2026.
Which one do you need?
Start from who is reading. Your customers and their tools, or your own coding agents.
Choose Mintlify if
- You need a public documentation site for developers who integrate with your product.
- You have an OpenAPI spec and want an interactive API reference and playground generated from it.
- You want other people's AI tools to search your docs through a hosted MCP server and llms.txt.
- Your docs already live in Markdown in Git and you want previews, a web editor, and a custom domain.
Choose ContextsBase if
- Your bottleneck is briefing Claude Code, Cursor, or Copilot on what to build, not explaining a finished product.
- You want business rules, entities, and edge cases stored once and served to every agent over MCP.
- You want agents to pull work from an ordered queue instead of pasting a prompt per task.
- You want tests that assert business rules, generated by the agent from plain-English cases.
- You want to know which shipped features are out of date the moment a spec changes.
Use both when
- Your product is built by agents and documented for agents. Specs go in ContextsBase; the resulting docs go in Mintlify.
- You want a clean handoff: a feature turns Implemented in ContextsBase, then a doc page describes it in Mintlify.
- Your team has a PM who owns specs and a DevRel or docs owner who owns prose. Each gets a tool shaped for the job.
Where each one sits when you use both
Specs flow forward into code. Docs describe the code once it exists. Neither tool has to know about the other.
01ContextsBase
Spec, entities, tests
02Your coding agent
Claude Code, Cursor, Copilot
03Your product
Feature turns Implemented
04Mintlify
Docs for your users' agents
Give your coding agent a spec to build from. Free.
The Free plan includes 1 project, 100 features, 3 members, 1 MCP token, and unlimited open iterations. Publish one feature, connect Claude Code or Cursor, and let it pull the first item.
Mintlify alternative FAQ
Short answers to the questions people ask before picking one, or both.
Also compared: ContextsBase vs Cursor rules. Or start at the home page.
Is ContextsBase a Mintlify alternative?
Only if your goal is to give your own coding agents context. ContextsBase holds features, business rules, entities, and test cases that agents like Claude Code and Cursor build from over MCP. It does not publish a documentation website. If you need a public docs site, Mintlify is the better fit, and many teams run both.
Does ContextsBase replace Mintlify?
No. They solve different problems. Mintlify publishes prose documentation for your users and their AI tools. ContextsBase is the structured spec and work queue for the agents writing your code. The output of a ContextsBase workflow is working software; the output of Mintlify is a documentation site.
Can I use Mintlify and ContextsBase together?
Yes. A common setup is: product decisions and business rules go into ContextsBase as features and test cases; your coding agent implements them and records the result; once a feature is Implemented, you write or generate the customer-facing page in Mintlify. Nothing in either tool blocks the other.
Does Mintlify work for coding agents?
Partly. Mintlify generates an MCP server, llms.txt, and Markdown endpoints so agents can search and read your published docs. Those tools are read-only. Mintlify does not provide a work queue, test cases, or a way for a coding agent to record what it implemented. That is the gap ContextsBase fills.
What does ContextsBase read from and write back over MCP?
Agents read published features, entities, flows, test cases, and theme tokens. They write back implementation records and test automation results. Tools include list_iterations, next_iteration_item, get_feature_spec, record_feature_implementation, and record_test_automation.
What does ContextsBase cost?
The Free plan includes 1 project, 100 features per project, 3 members, 1 MCP token, and unlimited open iterations. A Premium plan at $5 per month with unlimited projects, features, and members is coming soon.