How to Use the Typefully MCP in AutoGen

Q: How do I manage my drafts with Typefully and AutoGen?

Agents can use listdrafts to see everything, then call getdraftdetails to check specific content. They'll debate the best way to proceed before you manually intervene.

Q: Can I test publishing scenarios using Typefully and AutoGen?

Yes. You can have agents debate between calling publishimmediately versus setting a time with schedulecontent. It forces consensus on the best release timing.

Q: What if I need to confirm my social connections? (Typefully and AutoGen)

Running listsocialaccounts confirms all connected platforms. The agents treat this list as critical input when deciding where the content should go.

Debate your Typefully strategy with AutoGen: Consensus-driven publishing via MCP Server.

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Connect Typefully MCP to AutoGen

Create your Vinkius account to connect Typefully to AutoGen 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 AutoGen

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Drafting and Refining Content

Use the `create_draft` tool to generate initial content, then pass it through agents that debate its quality. You can later use `update_draft` if consensus requires changes to existing material. The system challenges assumptions about the draft's tone or length before finalizing the text.

Managing Publishing Decisions with AutoGen

Want to publish? The agents can debate whether it should happen immediately using `publish_immediately`, or if a delayed approach is better, calling `schedule_content`. This decision process ensures the best outcome. If a draft is bad, an agent can call `delete_draft` and justify why that content shouldn't go anywhere.

Reviewing Profile Data with AutoGen

Before posting anything, agents check your profile using `get_user_profile`. They also use `list_social_accounts` to confirm every platform is properly linked and ready for action. This multi-agent review process prevents accidental posts to the wrong channels.

Setup guide

Set up Typefully MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Typefully tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Typefully_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Typefully data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Typefully_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Typefully data")
    print(result.messages[-1].content)

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Common questions about Typefully MCP in AutoGen

Agents can use `list_drafts` to see everything, then call `get_draft_details` to check specific content. They'll debate the best way to proceed before you manually intervene.

Yes. You can have agents debate between calling `publish_immediately` versus setting a time with `schedule_content`. It forces consensus on the best release timing.

The server offers many actions: you can create, read, update, list drafts, or even retrieve your full user profile data.

Running `list_social_accounts` confirms all connected platforms. The agents treat this list as critical input when deciding where the content should go.

This MCP Server touches Draft content details, User Profile information, and Social Account connection status. The agents use all these data points during their deliberation process.

Use it with your favorite AI tools

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

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