Typefully MCP Server

The Typefully MCP Server bridges the gap between conversational AI assistants and the Typefully platform, enabling automated creation, scheduling, and management of Twitter threads directly from an AI workflow. By exposing a set of MCP tools—, , and —the server turns a standard Typefully account into a programmable resource that can be queried or mutated by any MCP‑compatible client such as Claude Desktop, Cursor, or custom bots.

At its core, the server solves a common pain point for social media managers: the repetitive and manual steps involved in drafting multi‑tweet threads, scheduling them for optimal engagement times, and tracking published content. Instead of toggling through a web interface, developers can embed these actions in natural language prompts or scripted routines. For example, an assistant could interpret a user’s request to “schedule a thread about the latest product launch for next free slot” and translate it into an API call that creates a properly formatted draft, applies automatic threadification, sets the desired schedule, and returns a shareable URL—all in a single conversational turn.

Key capabilities of the server include:

• Thread‑friendly drafting: Users can write long content separated by four newlines; the server automatically splits it into individual tweets, respecting Twitter’s character limits.
• Advanced scheduling: Drafts can be scheduled for a specific ISO‑formatted timestamp or automatically placed in the next available slot, simplifying time‑zone handling and avoiding conflicts.
• Engagement automation: Optional flags for AutoRT (auto‑retweet) and AutoPlug (automatic inclusion of relevant hashtags or mentions) allow the assistant to set up sophisticated posting strategies without manual intervention.
• Retrieval with filtering: The and tools support content type filters (tweets vs. threads), making it easy to audit or repurpose recent activity.

In real‑world scenarios, marketing teams can use the server to generate campaign threads from brief briefs, schedule them for peak audience times, and later fetch a list of published tweets to feed into analytics dashboards. Content creators can automate the release of weekly newsletters or product updates, while data scientists might pull recently published drafts to train sentiment models. Because the server integrates directly with the Typefully API, it inherits all native features such as threadification logic and scheduling accuracy, ensuring that automated posts behave exactly like manually crafted ones.

For developers, the MCP interface means seamless incorporation into existing AI pipelines. A single prompt can trigger multiple actions—draft creation, scheduling, and confirmation—all handled by the server. The MCP’s tool registry exposes each capability as a distinct callable, allowing fine‑grained control over parameters and easy error handling. Moreover, the server’s secure key management (macOS Keychain or environment variables) keeps credentials out of code, aligning with best practices for production deployments. Overall, the Typefully MCP Server offers a powerful, low‑friction bridge between conversational AI and Twitter content management, streamlining workflows and reducing manual overhead for social media professionals.