Typefully MCP Server for LlamaIndexGive LlamaIndex instant access to 9 tools to Create Draft, Delete Draft, Get Draft Details, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Typefully as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Typefully app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 9 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Typefully. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Typefully?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Typefully MCP Server
Connect your Typefully account to any AI agent and simplify how you draft, schedule, and publish high-engagement content for X (Twitter) and LinkedIn through natural conversation.
LlamaIndex agents combine Typefully tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Draft Management — List all your content drafts and retrieve detailed text and settings for specific ideas.
- Instant Publishing — Post content immediately to all your enabled social platforms directly via AI commands.
- Smart Scheduling — Schedule your posts for a specific time or use the 'next-free-slot' feature to optimize your queue.
- Account Directory — List all connected social sets and brands managed in your Typefully workspace.
- Draft Lifecycle — Create, update, and delete drafts programmatically to maintain your content pipeline.
- User Insights — Retrieve your profile details and verify account configurations directly from the agent.
The Typefully MCP Server exposes 9 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 9 Typefully tools available for LlamaIndex
When LlamaIndex connects to Typefully through Vinkius, your AI agent gets direct access to every tool listed below — spanning content-scheduling, social-media-management, threads, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new content draft
Remove a draft
Get details for a draft
Get your Typefully profile
List content drafts
List connected social accounts
Publish content right now
Schedule content for later
Modify an existing draft
Connect Typefully to LlamaIndex via MCP
Follow these steps to wire Typefully into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Typefully MCP Server
LlamaIndex provides unique advantages when paired with Typefully through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Typefully tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Typefully tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Typefully, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Typefully tools were called, what data was returned, and how it influenced the final answer
Typefully + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Typefully MCP Server delivers measurable value.
Hybrid search: combine Typefully real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Typefully to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Typefully for fresh data
Analytical workflows: chain Typefully queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Typefully in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Typefully immediately.
"List all my social accounts in Typefully."
"Publish this to my personal account now: 'Excited to announce our new MCP server! #AI #DevTools'"
"Show me all scheduled drafts for the 'Company News' account."
Troubleshooting Typefully MCP Server with LlamaIndex
Common issues when connecting Typefully to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTypefully + LlamaIndex FAQ
Common questions about integrating Typefully MCP Server with LlamaIndex.