How to Use the Discourse MCP in AutoGen
Build AutoGen agent teams that debate forum moderation decisions and analyze Discourse community trends.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Discourse MCP to AutoGen
Create your Vinkius account to connect Discourse 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.
Debate moderation actions using this MCP Server
The `get_user_profile` tool provides detailed member history to your AutoGen moderation team during automated MCP debates. A security agent reviews the profile details while a community manager agent evaluates the user's recent posts to reach a consensus. This multi-agent review prevents false positives and unfair bans. The agents discuss the user's standing and decide on the best course of action based on community guidelines.
Track trending discussions with AutoGen teams
The `list_trending_discussions` tool identifies high-engagement threads for your AutoGen analysis agents to review. One agent monitors the engagement metrics while another drafts a summary of the hot topics for your weekly newsletter. This cooperative approach ensures your community updates are accurate and engaging. The agents cross-reference the trending list with active forum categories to find the most relevant discussions.
Audit community groups in AutoGen workflows
The `list_group_members` tool allows your AutoGen security agents to audit user permissions across different forum groups. The agents compare the active member lists against your internal database to flag unauthorized accounts. This automated auditing keeps your community secure without manual hassle. The agents collaborate to flag discrepancies and output a clean report for your forum administrators.
Set up Discourse 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Discourse tools and returns structured results.
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="Discourse_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Discourse data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Discourse_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Discourse data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Discourse. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Discourse MCP in AutoGen
Use it with your favorite AI tools
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