You're a writer, a marketer, or a founder. You've just finished a brilliant 1,500-word blog post on your website. Now you need to also publish it on Medium because that's where your audience reads. So you log in, copy-paste the text, add headers, embed images, format code blocks, choose a teaser, then wait... The article looks slightly off. You fix it. Then you realize the tags didn't save. Then you need to schedule it for the next morning, and you wonder why you spend 40 minutes doing something a machine could do in 10 seconds.
That frustration is exactly what the ASI Biont AI agent removes. Instead of making you navigate yet another dashboard, ASI Biont connects directly to Medium through its official API. You just give it an access token in chat. The AI writes the integration code on the fly and then handles drafting, publishing, repurposing, and even routine performance checks — all through conversational commands.
In this article, I'll walk you through what this integration actually does, how it works, and how to set it up in less than five minutes — without manually writing a single line of code.
Why Medium and an AI agent are a natural fit
Medium is a publishing platform used by millions of readers monthly. For content teams, it's a syndication channel: you republish your existing articles to reach a broader audience. But the repetition involved — formatting, tagging, uploading, publishing — is exactly the kind of work that eats time and introduces errors.
Medium has a well-documented REST API, the official door for third-party applications. It lets you identify the authenticated user (GET /v1/me), list publications (GET /v1/users/:id/publications), and create posts (POST /v1/users/:id/posts). The API supports Markdown and HTML content, draft, public, and unlisted publishing statuses, up to five tags, and canonical URLs — useful for preserving SEO value. The authoritative specification is published at docs.medium.com.
Yet an API alone does not save you time. You still have to write the integration, handle authentication, and build the workflow. That's where a general-purpose AI agent like ASI Biont changes the game. Instead of a pre-built 'plugin' with narrow limits, the agent writes its own integration code against the API in real time, handles edge cases, and can perform multiple API calls in sequence.
What the ASI Biont integration automates
The AI agent can orchestrate any sequence of API calls. Concretely, here are the workflows you can ask for in natural language:
| Workflow | What the agent does with the Medium API |
|---|---|
| Draft generation | Takes your outline or raw notes, writes a structured article, and creates a Medium draft with publishStatus: draft |
| Publishing | Takes your final Markdown or HTML, sets tags and canonical URL, and publishes as public or unlisted (or creates a draft for review) |
| Publication submission | Lists your publications and submits a post to a specific publication |
| Repurposing | Converts a blog post, Google Doc, or video transcript into a Medium-optimized article |
| Batch posting | Publishes multiple articles sequentially with different titles and tags from a single chat command |
| Content verification | Confirms the post is live by fetching the user's feed or the public RSS output |
The important detail: the AI agent does not simply hit a single endpoint. It manages the OAuth 2.0 access token, sets the correct headers, encodes the content to the format Medium accepts, and gracefully handles error responses like validation messages or rate limits. You don't see this complexity; you only see the result.
Practical use cases
Let me make this tangible with three realistic scenarios.
1. Write once, publish everywhere
Your team publishes a weekly long-form article on your company's website. You copy the link and the text into ASI Biont, then say:
'Repurpose this article for Medium. Remove the internal promotion paragraphs, rewrite the first two sentences for a new audience, add tags productivity and software, and create it as a draft. Then show me a summary.'
The AI agent can fetch the content from your URL (it does that for many public pages), rewrite it, and make a single POST /v1/users/:id/posts call with publishStatus: draft. You review the draft in Medium, hit Publish, and you've saved 30–40 minutes of manual formatting.
2. Turning a YouTube video into a Medium post
Many content teams produce video first, then want a text version for readers who prefer scanning. ASI Biont can take a transcript file, structure it into sections, add headings, and publish it as a Medium article with a canonical URL pointing back to the original video page. This is a classic content repurposing pipeline:
- Upload or paste the video transcript.
- The AI structures it into a readable article with subheadings.
- The AI creates a draft on Medium with a search-friendly title.
- You approve; the AI changes the status to public in a follow-up call.
3. Submitting to a curated publication
If you write for a Medium publication with thousands of followers, you know every submission must fit the publication's style. The agent first lists your publications via GET /v1/users/:id/publications, then prepares a post specifically for that publication. It uses the POST /v1/publications/:publicationId/posts endpoint and includes the title and tags you define. No copy-paste, no risk of posting to the wrong profile.
How the integration works under the hood
To appreciate the engineering, let's look at a typical API call. When you ask ASI Biont to 'publish this draft', the agent constructs an HTTP request similar to this:
- Endpoint: POST https://api.medium.com/v1/users/{authorId}/posts
- Authorization header: Bearer {your_integration_token}
- Content-Type header: application/json
- Request body: title, contentFormat (either markdown or html), content, publishStatus, tags, and optional canonicalUrl.
If you are publishing to a Medium publication, the endpoint becomes POST https://api.medium.com/v1/publications/{publicationId}/posts. The response returns the post's URL and id, which the AI agent can display in chat or save for later tracking.
The integration token is an access token generated in Medium's settings. It acts as an API key scoped to your account. You never need to pass a password; the token is enough for the agent to act on your behalf.
Here's a quick reference of the most useful API endpoints:
| Endpoint | Purpose |
|---|---|
| GET /v1/me | Get the authenticated user's id and profile information |
| GET /v1/users/:id/publications | List publications the user contributes to |
| POST /v1/users/:id/posts | Create a post on the user's profile |
| POST /v1/publications/:id/posts | Create a post in a specific publication |
One practical note: ASI Biont can also maintain a small state file or a database of your published posts, so it can check for duplicate names or keep a content calendar. This is all done inside the chat conversation.
How to connect: no dashboard, only chat
Most integration platforms ask you to go to a settings page, click 'Add Integration', choose from a list, and fill a form. ASI Biont takes a different approach — one that works for any service with a public API.
Here is the whole setup process:
-
Get a Medium integration token.
Log in to Medium, go to Settings → Security and applications → Integration token, and generate a token. It is a long alphanumeric string. -
Paste the token into chat.
In your ASI Biont chat window, send something like:
Here's my Medium token: [token]. Can you set up publishing for me? -
The AI agent writes the integration code on the fly.
The AI agent reads the official API documentation, writes the authentication logic (often a small Python script using the requests library or a TypeScript equivalent), verifies the token against GET /v1/me, and confirms the connection. From that moment, you can say things like 'publish this as an unlisted post' or 'create a draft titled X'.
There is no separate integrations page in ASI Biont. No pre-built connectors to wait for. The agent acts as a software engineer that builds the integration for you on request, the same way a human developer would — only in real time and with no human in the loop.
This approach has a huge advantage: Medium is not special-cased. The same mechanism works for Notion, WordPress, Slack, Shopify, or any service with a REST API. You simply provide the API key or access token, and the agent adapts. You never have to wait for a platform to add support for a new service.
Limitations of the official API and pragmatic workarounds
The official Medium API is intentionally limited. It allows publishing and user management, but it does not provide endpoints for reading article analytics (views, reads, read ratio) or editing an existing post. The current capabilities are confirmed in the official API documentation at docs.medium.com.
ASI Biont works around this in two ways:
- Public metrics: For public information, the agent can fetch the RSS feed at medium.com/feed/@username. This reveals titles, URLs, and publish dates — enough to confirm a post is live and to build a simple content calendar.
- Private analytics: The agent can connect to additional services you already use, such as Google Analytics or a custom metrics endpoint, and merge that data with the publishing records from your chat session.
To be clear, the integration does not pretend to have features the Medium API does not expose. But it does give you a repeatable engineering solution using real, documented endpoints.
Who benefits most
| Persona | Typical command in chat | Value |
|---|---|---|
| Blogger | 'Format this draft into a Medium post and create a draft for me' | Saves 15–30 minutes per article |
| Marketing lead | 'Publish today's case study to both our blog and Medium with a canonical URL' | Removes copy-paste errors and keeps SEO consistent |
| Content operations specialist | 'Take these five video transcripts and turn them into Medium drafts for review' | Turns hours of manual work into minutes |
| Growth hacker | 'Publish this article as unlisted, then give me the link for a private audience' | Makes publishing repeatable and fast |
The pattern is always the same: mundane formatting and API engineering happen behind the scenes, while you focus on message and strategy.
Security and best practices
When connecting any third-party tool, treat your Medium integration token as a password. Do not paste it into public forums. ASI Biont receives it only in your private chat session. After the connection is established, you can revoke the token from Medium's settings at any time; the agent will then no longer have access.
A few practical recommendations:
- Use a dedicated token for each automation workflow, so you can revoke it independently.
- Start with publishStatus: draft until you are comfortable with the generated output.
- Ask the agent to show the API request before publishing if you want full transparency.
- Keep a backup of your source content; just because a post is drafted does not mean it is stored in your CMS.
These are standard hygiene practices that make automation safe.
Start your first automated Medium post today
The fastest way to evaluate this integration is to use a throwaway article. Generate a Medium integration token, open asibiont.com, and type:
'Connect to Medium using this token, then create a draft post titled Testing Automation with a couple of paragraphs of good content.'
Watch how the agent builds the connection, makes the API call, and replies with a confirmation and a link to your draft. You've just automated your first Medium publication.
Once you see it work, scale up: connect your blog's RSS feed, repurpose your YouTube content, or build a complete editorial pipeline that runs from a single chat conversation. That is the real power of AI integration — not a dozen disconnected tools, but one agent that builds bridges and runs them for you.
Try it now at asibiont.com.
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