Skip to main content
Glama
vidhupv

X(Twitter) MCP Server

by vidhupv

create_draft_tweet

Create draft tweets for X/Twitter by providing content, enabling users to prepare posts for review and scheduling through the chat interface.

Instructions

Create a draft tweet

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe content of the tweet

Implementation Reference

  • The handler function that executes the create_draft_tweet tool. It validates the input arguments, creates a draft by saving the tweet content to a local JSON file with a unique ID, logs the action, and returns a success message with the draft ID.
    async def handle_create_draft_tweet(arguments: Any) -> Sequence[TextContent]:
        if not isinstance(arguments, dict) or "content" not in arguments:
            raise ValueError("Invalid arguments for create_draft_tweet")
        content = arguments["content"]
        try:
            # Simulate creating a draft by storing it locally
            draft = {"content": content, "timestamp": datetime.now().isoformat()}
            # Ensure drafts directory exists
            os.makedirs("drafts", exist_ok=True)
            # Save the draft to a file
            draft_id = f"draft_{int(datetime.now().timestamp())}.json"
            with open(os.path.join("drafts", draft_id), "w") as f:
                json.dump(draft, f, indent=2)
            logger.info(f"Draft tweet created: {draft_id}")
            return [
                TextContent(
                    type="text",
                    text=f"Draft tweet created with ID {draft_id}",
                )
            ]
        except Exception as e:
            logger.error(f"Error creating draft tweet: {str(e)}")
            raise RuntimeError(f"Error creating draft tweet: {str(e)}")
  • Registers the 'create_draft_tweet' tool in the list_tools() function, including its name, description, and input schema.
    Tool(
        name="create_draft_tweet",
        description="Create a draft tweet",
        inputSchema={
            "type": "object",
            "properties": {
                "content": {
                    "type": "string",
                    "description": "The content of the tweet",
                },
            },
            "required": ["content"],
        },
    ),
  • Defines the JSON schema for the tool's input, requiring a 'content' property of type string.
    inputSchema={
        "type": "object",
        "properties": {
            "content": {
                "type": "string",
                "description": "The content of the tweet",
            },
        },
        "required": ["content"],
    },
  • Dispatches the tool call to the specific handler function in the general call_tool handler.
    if name == "create_draft_tweet":
        return await handle_create_draft_tweet(arguments)

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/vidhupv/x-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server