How to Use the Keepcon MCP in LangChain

Q: Can LangChain handle batch processing with the Keepcon MCP Server?

Yes. You can chain importbatch to start the job and then poll exportresults to collect data. It works well for large volume tasks.

Chain Keepcon moderation tasks directly into your LangChain agents for automated, multi-step content decision pipelines.

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Connect Keepcon MCP to LangChain

Create your Vinkius account to connect Keepcon to LangChain 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 Keepcon with LangChain

Ask AI about this MCP

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Claude

Perplexity

Chain moderation into your LangChain agents

Connect your agent to `import_batch` and `moderate_content` to build automated pipelines. Your agent handles the logic, deciding when to push data and how to act on the output. Every decision flows through your LangSmith traces. You see exactly how the agent navigated the `moderate_content` results to flag or clear posts.

Automated feedback loops for your MCP Server

Feed moderation decisions back into the platform using `submit_feedback`. Your agent identifies false positives and triggers this tool to tune the semantic engine automatically. This keeps your moderation logic sharp without manual intervention. It's a closed-loop system where your agent learns from every moderation event.

Direct profile management via MCP tools

Query specific users with `get_profile` or `get_profile_by_social_id` during a chain. Your agent pulls the necessary context before deciding on a moderation action. This gives your pipeline deep situational awareness. It isn't just flagging text; it's looking up the user history before making a final call.

Setup guide

Set up Keepcon MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Keepcon tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "keepcon-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Keepcon transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Keepcon. 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 Keepcon MCP in LangChain

Use the langchain-mcp-adapters package to pull tools from the server. Once initialized, pass them into your agent definition so it can invoke functions like `moderate_content`.

Yes. You can chain `import_batch` to start the job and then poll `export_results` to collect data. It works well for large volume tasks.

Yes, use the client.session() method to keep state across your agent's interactions. This ensures the server remembers your context during complex investigations.

Every call to a Keepcon tool is logged through your standard LangSmith provider. You get full visibility into inputs and the raw outputs from the API.

The server processes user profile and content data strictly via your authorized endpoint. No data is stored on Vinkius infrastructure; it acts only as a secure bridge for your requests.

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