How to Use the Reportei MCP in LangChain

Q: Can LangChain automate client onboarding using Reportei?

Yes. Your agent can run listclients to check existing accounts and then use getclient to verify connection details. This lets you build onboarding chains that run without manual intervention.

Q: Can I filter specific projects inside a LangChain runnable?

Yes. Your agent can use listreporteiprojects to find the correct project ID. It then passes that ID to listreporteireports to filter and retrieve the exact documents needed for the active run.

Build multi-step reporting pipelines in LangChain to generate Google and Facebook marketing reports in minutes.

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…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Reportei MCP to LangChain

Create your Vinkius account to connect Reportei to LangChain — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Reportei with LangChain

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Chain raw marketing metrics directly into LangChain agents

The Reportei MCP Server allows LangChain agents to fetch live performance data across multiple ad platforms with a single call. By exposing `get_reportei_metrics` and `list_integrations`, this MCP Server lets your agent inspect active channels and pull raw numbers directly into a running chain. You don't have to write custom API wrappers for Google or Facebook anymore. The agent evaluates the current performance, decides which metrics are missing, and pulls them dynamically to feed the next step in your reasoning loop.

Automate report generation with LangSmith observability

This MCP Server automates the generation of polished marketing reports directly within your LangChain workflows. The agent triggers `create_report` after gathering the necessary context, giving you a finished document ready for presentation. Because each step runs through LangChain, you can trace the entire execution path in LangSmith. You see exactly when `list_reportei_reports` was called, what parameters were passed, and how long the generation took.

Log custom agency milestones into client timelines

This marketing integration lets your LangChain agents log custom milestones directly to your agency feeds. Using `add_reportei_event`, your chain can log when an ad campaign was paused or when a budget cap was hit. This turns your workflows into an active log book. The agent checks existing notes with `list_reportei_timeline` before taking action, ensuring it never duplicates work or runs conflicting tasks.

Setup guide

Set up Reportei 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 Reportei 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({
    "reportei-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 Reportei 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 Reportei. 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 Reportei MCP in LangChain

Use the MultiServerMCPClient from the LangChain MCP adapter package pointing to your Vinkius endpoint. Call get_tools to retrieve the tools and pass them directly to your agent constructor.

Yes. Your agent can run list_clients to check existing accounts and then use get_client to verify connection details. This lets you build onboarding chains that run without manual intervention.

The server manages platform API quotas behind the scenes. Your LangChain chains will receive clean JSON responses, and you can configure standard LangChain retry runnables to handle transient network issues.

Yes. Your agent can use list_reportei_projects to find the correct project ID. It then passes that ID to list_reportei_reports to filter and retrieve the exact documents needed for the active run.

All sensitive API keys and marketing platform tokens are held securely in the Vinkius sandbox. The server only passes raw analytical metrics like click-through rates and spend data to your local LangChain environment.

Use it with your favorite AI tools

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