Can I retrieve social mentions for a specific date range?

Yes! Use the `get_mentions` tool with the Project ID, Query ID, and your ISO 8601 formatted start and end dates (e.g., 2024-01-01T00:00:00.000Z).

How do I see the volume trend of a query over time?

Simply ask the agent to `get_volume_aggregates` and provide the relevant IDs and date range. It will return the aggregated data points showing mention spikes.

Does the integration allow creating new boolean queries?

Currently, the toolset is focused on reading and retrieving data from existing setups. Creating complex boolean queries should be done via the Brandwatch web interface to utilize their query builder and syntax validation.

Brandwatch MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Brandwatch
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Brandwatch 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({
        "brandwatch": {
            "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 Brandwatch, 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 Brandwatch MCP Server

Connect your Brandwatch Consumer Research account to any AI agent and orchestrate your social listening and data analysis workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Brandwatch through native MCP adapters. Connect 8 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

Project & Dashboard Navigation — List and retrieve detailed metadata for all your active research projects and dashboards.
Query Management — Access your configured search queries to monitor brand health and industry trends.
Mention Retrieval — Query and inspect raw social mentions based on specific queries and date ranges.
Data Aggregation — Retrieve volume aggregates to analyze mention trends and spikes over time.
Tag Coordination — List and create categorization tags to organize your social data effectively.

The Brandwatch MCP Server exposes 8 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 Brandwatch to LangChain via MCP

Follow these steps to integrate the Brandwatch 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 8 tools from Brandwatch via MCP

Why Use LangChain with the Brandwatch MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Brandwatch 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 Brandwatch queries for multi-turn workflows

Brandwatch + LangChain Use Cases

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

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

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

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

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

Brandwatch MCP Tools for LangChain (8)

These 8 tools become available when you connect Brandwatch to LangChain via MCP:

create_tag

Create a new tag for categorizing mentions

get_mentions

Retrieve mentions for a specific query

get_project

Get details of a specific project

get_volume_aggregates

Get mention volume aggregates for a query

list_dashboards

List dashboards in a project

list_projects

List all active projects

list_queries

List configured queries in a project

list_tags

List tags available in a project

Example Prompts for Brandwatch in LangChain

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

"List all queries configured in project proj_1."

"Get volume aggregates for query q_1 from Jan 1st to Jan 31st."

"Create a new tag called 'Urgent Review' in project proj_1."

Troubleshooting Brandwatch MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Brandwatch + LangChain FAQ

Common questions about integrating Brandwatch 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.