How to Use the Cilium (eBPF Networking) MCP in LangChain

Chain Cilium (eBPF Networking) operations directly into your LangChain reasoning pipelines.

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Connect Cilium (eBPF Networking) MCP to LangChain

Create your Vinkius account to connect Cilium (eBPF Networking) 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 Cilium (eBPF Networking) with LangChain

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Chain cluster insights in LangChain

Connect your agent to `get_cluster_nodes` to pull real-time topology data into your chains. You stop guessing about cluster state when your agent pulls the raw node list directly into its reasoning loop. Your chain processes these outputs as serialized nodes, letting you build automated diagnostics. The agent evaluates the data and decides the next step without you manually parsing JSON.

Automated daemon management for LangChain

Use `patch_config` to adjust your Cilium daemon settings based on live chain feedback. The agent modifies your network configuration in response to upstream events. This creates a closed-loop control system where your network adapts itself. You define the logic, and the agent executes the configuration changes.

Monitor Cilium (eBPF Networking) health in LangChain

Call `get_healthz` to feed daemon status into your LangSmith traces. You get a clear history of network health checks interleaved with your agent's decision logic. This visibility helps you spot issues before they cascade through your chain. You see exactly what the agent saw when it made a specific networking decision.

Setup guide

Set up Cilium (eBPF Networking) 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 Cilium (eBPF Networking) 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({
    "cilium-ebpf-networking-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 Cilium (eBPF Networking) transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Cilium (eBPF Networking) MCP in LangChain

LangChain integrates with LangSmith to log every tool input and output. You see exactly what the agent received from the server and what it sent back.

Yes, it uses the provided tools to modify daemon settings. You define the policy, and your agent handles the execution.

By default, the client is stateless. You must use a session if you need to keep context across multiple calls.

You provide a single endpoint token to the Vinkius gateway. All requests are signed and routed securely to your infrastructure.

This server touches cluster configuration, node metadata, and daemon health metrics. The connection is restricted to these specific diagnostic endpoints for your safety.

Use it with your favorite AI tools

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