8 Solo Developer Pitfalls When Exposing Scheduling APIs to AI Agents

AI Summary · Perspective of a Serial Entrepreneur (The following content is distilled by AI; viewpoints belong to the original author; reading the full text is optional.)

A solo developer exposed their social scheduling SaaS API via MCP for use by Claude and Cursor. After logging 700–800 real-world calls per day, they outlined eight practical lessons that never make it into demo videos. The core counterintuitive insight: interacting with an Agent is harder than interacting with a human. Success requires mandatory pre-validation, idempotency keys, approval workflows, and hardcoded platform limits—not reliance on Agent intelligence.

• Reject black-box trust: account association ambiguity demands a forced List Accounts call for verification; never let the Agent guess.
• Front-load error interception: media files (TikTok/IG) must be validated for size and format at creation time to avoid failures at publish time.
• Prevent duplication: the Create endpoint must include an Idempotency Key, or retries will result in duplicate posts.
• Async decoupling: MCP only schedules the post; publishing is executed by a server-side Job…
• Toolize the approval flow: Pending status must be its own independent Tool…

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I run a small social scheduling SaaS on my own. A few months ago I shipped an MCP server so Claude, ChatGPT and Cursor could schedule posts through the same API the app uses. It is used for real now, roughly 700 to 800 connector calls a day at the CDN last week, none of them mine. What follows is the list of things that were different from the demo, in the order they bit. The agent does not know which account you meant. The moment a brand has two Facebook Pages or two LinkedIn orgs, 'post this to LinkedIn' is ambiguous. Every post now has to carry one account id, and the tool description tells the agent to list accounts first and check that the account is still connected. Disconnected accounts were already the number one cause of failed posts for humans. Agents made it worse because they do not notice the red badge. Validate at create time, not at fire time. A scheduled post fails hours after the agent finished talking, and nobody is there to read the error. So media is required at create time on the platforms that need it (TikTok, YouTube, Instagram, Pinterest), even for drafts, the media type has to match the file, and size caps are enforced on upload. The agent gets the rejection while it can still fix it. Retries duplicate. Our create call has no idempotency key. If the transport drops and the agent retries, you get two scheduled posts. Listing and deleting posts are tools too, so the agent can clean up, but that is the honest gap and it is next on the list. Do not make the agent wait for the publish. The MCP call only creates the scheduled post; publishing runs later as a server job. A 200MB video never sits on the MCP transport, which is where every timeout report we saw came from. Approvals need to be a tool, not a dashboard. Posts can be created as pending approval, and either a person or the agent, via an approve call, moves them to approved. Nothing publishes while pending. Without this, teams turn the agent off after the first wrong post. Some platform limits should be enforced by you, not discovered by the agent. X charges far more for posts with links, so we cap link posts per month per plan. An agent that loves adding links hits the cap on purpose. Assistants quote your docs verbatim. When someone asks ChatGPT for a scheduler with an MCP server, the answer lists the vendors whose pages print the endpoint URL and the setup steps in plain text. Pages that describe the feature in marketing language are skipped. We rewrote ours accordingly, and it is the cheapest change on this list. Live-data features are hard to get through app-store revi

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