How do I get a Determ API Key?

Log in to your Determ account, navigate to **Settings > API**, and you can retrieve your unique API Key from that section.

Can the agent show the full text of an article?

Yes, you can use the get_mention_details tool to retrieve the full content and metadata for a specific mention found by Determ.

Is real-time monitoring supported?

Yes, the list_media_mentions tool retrieves the most recent mentions based on your query settings, providing real-time data from the Determ platform.

Determ MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Determ
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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({
        "determ": {
            "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 Determ, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 Determ MCP Server

Integrate Determ (formerly Mediatoolkit), the powerful media monitoring and social listening platform, directly into your AI workflow. Track brand mentions across the web and social media, analyze sentiment trends, and monitor your competitive landscape using natural language.

LangChain's ecosystem of 500+ components combines seamlessly with Determ through native MCP adapters. Connect 10 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

Mention Monitoring — List and retrieve real-time media mentions for your keywords and topics from over 100 million sources.
Sentiment Intelligence — Retrieve a breakdown of sentiment (positive, neutral, negative) for any of your monitoring queries.
Query Management — List and review your configured monitoring queries and their specific settings.
Analytics Reporting — Access metadata for your media monitoring and analytics reports directly via chat.

The Determ MCP Server exposes 10 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.

How to Connect Determ to LangChain via MCP

Follow these steps to integrate the Determ MCP Server with LangChain.

Install dependencies

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

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Determ via MCP

Why Use LangChain with the Determ MCP Server

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

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

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

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

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

Determ + LangChain Use Cases

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

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

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

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

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

Determ MCP Tools for LangChain (10)

These 10 tools become available when you connect Determ to LangChain via MCP:

get_account_metadata

Retrieve settings and limits for your Determ account

get_mention_details

Get full content and technical metadata for a specific media mention

get_monitoring_query_details

Get detailed settings and status for a specific monitoring query

get_query_sentiment_summary

Retrieve a breakdown of sentiment (positive, neutral, negative) for a specific query

list_analytics_reports

List all available analytics and media monitoring reports

list_media_mentions

List recent media mentions for a specific monitoring query

list_monitoring_queries

List all media monitoring queries (keywords/topics) in your Determ account

list_recent_high_reach_mentions

List only the mentions with the highest estimated reach

list_top_media_sources

Identify the media sources with the highest volume of mentions (mock logic)

search_mentions_by_keyword

Search for specific keywords within the mentions of a monitoring query

Example Prompts for Determ in LangChain

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

"List my active monitoring queries."

"Show me the sentiment breakdown for the 'Main Competitor' query."

"What are the top media sources for 'Industry Trends'?"

Troubleshooting Determ MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Determ + LangChain FAQ

Common questions about integrating Determ MCP Server with LangChain.

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.

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.