How to Use the Alegra MCP in LangChain

Q: How do I pass Alegra tools to a LangChain agent?

Install the adapter first. Initialize the client, call gettools, and pass them to your agent constructor. The agent will automatically select tools like createinvoice when tax actions are needed.

Q: How do I trace Alegra tool inputs in LangChain?

Connect your project to LangSmith. Every call to getinvoicedetails or listpayments gets logged automatically. You can inspect the exact JSON payloads and latency of each call.

Run your Latin American accounting pipelines by chaining Alegra tools directly inside your LangChain agents.

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Connect Alegra MCP to LangChain

Create your Vinkius account to connect Alegra 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 Alegra with LangChain

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Chain tax compliance into LangChain pipelines

Let your LangChain agent pull items using `list_inventory_items` and immediately feed those details into `create_invoice`. You don't have to write glue code to pass Latin American tax data between steps. This MCP Server exposes raw financial tools to your runtime. Since LangChain handles state across complex chains, your agent checks `get_invoice_details` and decides whether to trigger a payment log via `list_payments` without manual intervention.

Track Alegra MCP Server steps with LangSmith

Track how your agent calls `create_contact` and `create_invoice` directly inside LangSmith. You see the exact payload sent to Alegra and the raw response payload in your tracing dashboard. Having this visibility prevents silent failures during automated billing runs. If a tax ID is missing during `get_contact_details`, you spot the exact node in your LangChain graph that failed before it hits your production logs.

Automate invoice reconciliation flows

Run automated LangChain reconciliation loops by querying `list_invoices` to find unpaid bills. After fetching client records via `list_contacts`, your agent compiles everything into a single report. You combine these accounting tools with database writes or email nodes in the same LangChain execution. If `get_company_info` returns matching tax parameters, the agent proceeds to log the payment details instantly.

Setup guide

Set up Alegra 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 Alegra 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({
    "alegra-extended-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 Alegra transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Alegra MCP in LangChain

Install the adapter first. Initialize the client, call get_tools, and pass them to your agent constructor. The agent will automatically select tools like `create_invoice` when tax actions are needed.

Yes, it manages the sequential logic perfectly. Your agent queries tax rules using `get_company_info` and applies them when executing `create_invoice`. This ensures your electronic invoices comply with local regulations.

Connect your project to LangSmith. Every call to `get_invoice_details` or `list_payments` gets logged automatically. You can inspect the exact JSON payloads and latency of each call.

Yes, the MultiServerMCPClient lets you aggregate this toolset with other APIs. Your agent can query a database, then immediately run `create_contact` on Alegra via this Vinkius MCP connection.

Your invoice details, payments, and contact records never pass through third-party LLM servers. Vinkius runs this MCP Server in an isolated sandboxed environment. Your API keys are kept encrypted and are only used to sign requests directly to the billing endpoint.

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