pepuscz/typefully-mcp-server
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The Typefully MCP Server is a Model Context Protocol server that integrates with the Typefully API, enabling AI assistants to manage and create drafts on Typefully.
The Typefully MCP Server is designed to facilitate seamless integration with the Typefully API, allowing users to automate the creation and management of drafts on the Typefully platform. This server supports a range of features including the creation of multi-tweet threads, automatic threadification, and scheduling of drafts. Users can also enable AutoRT and AutoPlug features for their posts, and share URLs directly from the server. The server is built with Python and requires a Typefully account with API access. It offers secure API key storage using macOS Keychain or environment variables, ensuring compatibility and security. The server is easy to install and configure, with detailed instructions provided for setting up the MCP client. It also includes a test script to verify functionality, making it a reliable tool for managing Typefully drafts.
Features
- Create drafts with multi-tweet threads and automatic threadification
- Schedule drafts for specific dates/times or next free slot
- Enable AutoRT and AutoPlug features for posts
- Share URLs directly from the server
- Secure API key storage using macOS Keychain or environment variables
Usages
usage with cursor
{ "mcpServers": { "typefully": { "command": "/path/to/your/typefully-mcp-server/venv/bin/python", "args": ["-m", "typefully_mcp_server.server"], "cwd": "/path/to/your/typefully-mcp-server" } } }
usage with claude desktop
{ "mcpServers": { "typefully": { "command": "/path/to/your/typefully-mcp-server/venv/bin/python", "args": ["-m", "typefully_mcp_server.server"], "cwd": "/path/to/your/typefully-mcp-server" } } }
Tools
create_draft
Create a new draft in Typefully with options for threadification, scheduling, and sharing.
get_scheduled_drafts
Retrieve recently scheduled drafts with optional content filtering.
get_published_drafts
Retrieve recently published drafts with optional content filtering.