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DataScope MCP Server for LangChainGive LangChain instant access to 6 tools to Get Submission Pdf Url, Get Submissions With Metadata, List Available Forms, and more

Built by Vinkius GDPR 6 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect DataScope through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this App Connector for LangChain

The DataScope app connector for LangChain is a standout in the Productivity category — giving your AI agent 6 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "datascope": {
            "transport": "streamable_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,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using DataScope, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
DataScope
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About DataScope MCP Server

Connect your DataScope account to any AI agent and take full control of your mobile form data collection and field operations through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with DataScope through native MCP adapters. Connect 6 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

  • Submission Orchestration — List and retrieve form submissions (answers) programmatically, using powerful filters for form IDs, users, and date ranges
  • Field Data Intelligence — Access detailed metadata for every submission, including question types and internal identifiers to coordinate data analysis
  • Form & User Architecture — Retrieve complete directories of available forms and registered organization users to oversee team collaboration in the field
  • Asset Retrieval — Programmatically retrieve secure PDF download URLs for specific form submissions to streamline reporting and auditing workflows
  • Visual Monitoring — Access tracked locations and field data collection points directly through your agent to maintain high-fidelity operational transparency

The DataScope MCP Server exposes 6 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 DataScope tools available for LangChain

When LangChain connects to DataScope through Vinkius, your AI agent gets direct access to every tool listed below — spanning mobile-forms, field-inspections, data-collection, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

get_submission_pdf_url

Get PDF URL for a submission

get_submissions_with_metadata

List submissions with detailed metadata

list_available_forms

List available forms

list_form_submissions

You can filter by form ID or user ID. List form submissions (answers)

list_organization_users

List all users in the organization

list_tracked_locations

List tracked locations

Connect DataScope to LangChain via MCP

Follow these steps to wire DataScope into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 6 tools from DataScope via MCP

Why Use LangChain with the DataScope MCP Server

LangChain provides unique advantages when paired with DataScope through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine DataScope MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across DataScope queries for multi-turn workflows

DataScope + LangChain Use Cases

Practical scenarios where LangChain combined with the DataScope MCP Server delivers measurable value.

01

RAG with live data: combine DataScope tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query DataScope, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain DataScope tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every DataScope tool call, measure latency, and optimize your agent's performance

Example Prompts for DataScope in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with DataScope immediately.

01

"List the last 5 form submissions for form ID '1024'."

02

"Show me all registered users in my DataScope organization."

03

"Get the PDF download link for submission ID 'ans_789'."

Troubleshooting DataScope MCP Server with LangChain

Common issues when connecting DataScope to LangChain through the Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

DataScope + LangChain FAQ

Common questions about integrating DataScope MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.