How to Use the Scoro MCP in LangChain

Build LangChain agents that chain Scoro project data and invoice lists into automated billing pipelines.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Scoro MCP to LangChain

Create your Vinkius account to connect Scoro 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 Scoro with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Build Multi-Step Scoro Pipelines in LangChain

This Scoro MCP Server connects your project updates directly to LangChain billing workflows. Your agent can call `list_projects` to find active jobs, then immediately feed those IDs into `list_time_entries` to pull unbilled hours. This removes manual data hopping. Because every tool call is a link in a chain, the output of one Scoro query feeds the next step. You get complete visibility through LangSmith tracing to watch how your agent handles token usage and tool inputs.

Audit Project Expenses and Quotes

This budget analysis tool compares active sales quotes from `list_quotes` against real-time outgoing costs from `list_expenses`. The agent checks the numbers side-by-side without you writing custom glue code. It spots budget overruns early by comparing live Scoro financial records against your project scopes. You don't have to manually export CSVs to see the damage.

Track Team Utilization and Calendars

This resource tracking tool queries `list_calendar_events` and `list_tasks` in a single run to keep your team's schedule balanced. The agent identifies scheduling conflicts and flags team members who are double-booked. By matching these calendars with logged hours from `list_time_entries`, you get a clear picture of actual work versus planned events. It helps project managers allocate resources based on real historical data.

Setup guide

Set up Scoro 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 Scoro 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({
    "scoro-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 Scoro 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 Scoro. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Scoro MCP in LangChain

You pass your Scoro API key and site URL as environment variables when initializing the MultiServerMCPClient in LangChain. Vinkius handles the underlying secure transport so your agent can execute queries without hardcoded credentials.

Yes, LangChain agents use the ReAct framework to decide which tools to call sequentially. An agent can run `list_projects` to locate a client, then call `get_contact` to pull their details, all in one execution loop.

Use LangSmith tracing to observe every tool call your LangChain agent makes to Scoro. This lets you track exactly how often tools like `list_activities` are queried and prevent hitting API limits.

Yes, the MultiServerMCPClient lets you combine this Scoro MCP server with database or communication tools. Your agent can pull invoices using `list_invoices` and pass that data directly to a Slack or database tool.

Your Scoro invoices, expense reports, and contact records never persist on Vinkius. The MCP server runs inside an ephemeral, zero-trust V8 sandbox that destroys itself immediately after your LangChain agent finishes its tool execution.

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