How to Use the Typefully MCP in LlamaIndex

Q: How does LlamaIndex help with Typefully drafts?

The tool indexes every draft action. When you call updatedraft, the new text is added to a searchable knowledge base, so your agent can reference specific wording later.

Q: Can I track my content history using Typefully and LlamaIndex?

Absolutely. By indexing all tool outputs—like successful schedulecontent calls or deleted drafts via deletedraft—you build a queryable record of everything that happened.

Q: What tools are available for Typefully and LlamaIndex?

You can manage content using createdraft, listdrafts, getdraftdetails, and even run publishimmediately to capture the action in your index.

Q: What if I want to see my connected accounts? (Typefully and LlamaIndex)

Just use listsocialaccounts. This output is immediately added to the knowledge base, so you can query it later without having to run the tool again.

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Connect Typefully MCP to LlamaIndex

Create your Vinkius account to connect Typefully to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Typefully with LlamaIndex

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Managing Drafts via MCP Server

The `create_draft` tool lets you instantly write a new piece of content that the index can later search against. You can also run `list_drafts`, which feeds the full list into your knowledge base for context. Need to change something? The `update_draft` tool modifies existing material, and this new data gets indexed so future queries are accurate.

Scheduling Content with LlamaIndex

If you want to set a post for the future, use `schedule_content`. This action is captured as an event in your knowledge index. The agent can later query this data to confirm when and where it will go live. It makes sure that scheduled posts aren't missed or forgotten by linking them directly to past operational data.

Checking Content Status with LlamaIndex

Run `get_draft_details` when you want a deep dive into one draft. This provides all the specific content details that are then added to your searchable knowledge index. If you ever need to know what accounts you've connected, running `list_social_accounts` puts those connections right into your RAG application.

Setup guide

Set up Typefully MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Typefully MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Typefully tools.",
)
response = await agent.run("List recent Typefully data")

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Common questions about Typefully MCP in LlamaIndex

The tool indexes every draft action. When you call `update_draft`, the new text is added to a searchable knowledge base, so your agent can reference specific wording later.

Absolutely. By indexing all tool outputs—like successful `schedule_content` calls or deleted drafts via `delete_draft`—you build a queryable record of everything that happened.

You can manage content using `create_draft`, `list_drafts`, `get_draft_details`, and even run `publish_immediately` to capture the action in your index.

Just use `list_social_accounts`. This output is immediately added to the knowledge base, so you can query it later without having to run the tool again.

This MCP Server handles Draft content details, User Profile information, and Social Account connection status. All of these types become part of your unified index.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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