How do I generate an API token in Quantive?

Log in to your Quantive account, navigate to **Setup > Configuration > API tokens**, and click 'Generate token'. You'll need to select a user for the token's permissions.

Which data center should I select?

Check your browser URL when logged in. If it says `app.us.quantive.com`, select **US**. If it says `app.eu.quantive.com`, select **EU**.

Can I update the progress of my Key Results through this integration?

Yes! Use the `update_key_result` tool to set the current numeric value of any KR, and Quantive will automatically calculate the attainment percentage.

Does this integration support multiple sessions?

Yes. You can list all active and past sessions using `list_sessions`, allowing you to query OKRs from different timeframes as needed.

Quantive (Gtmhub) MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Quantive (Gtmhub)
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 Quantive (Gtmhub) 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({
        "quantive-gtmhub": {
            "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 Quantive (Gtmhub), 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 Quantive (Gtmhub) MCP Server

Connect your Quantive (formerly Gtmhub) strategy platform to any AI agent and drive your organizational goals through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Quantive (Gtmhub) 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

Objective Tracking — List and inspect strategic objectives to align your team's focus.
Key Result Management — Monitor progress on KRs and update current values directly from your chat or IDE.
Session Overview — Browse planning sessions and timeframes to understand quarterly or annual goals.
Team & User Insights — Retrieve team structures and user profiles to facilitate better collaboration.
Task Execution — List tasks linked to specific OKRs to bridge the gap between strategy and execution.

The Quantive (Gtmhub) 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 Quantive (Gtmhub) to LangChain via MCP

Follow these steps to integrate the Quantive (Gtmhub) 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 Quantive (Gtmhub) via MCP

Why Use LangChain with the Quantive (Gtmhub) MCP Server

LangChain provides unique advantages when paired with Quantive (Gtmhub) through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Quantive (Gtmhub) 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 Quantive (Gtmhub) queries for multi-turn workflows

Quantive (Gtmhub) + LangChain Use Cases

Practical scenarios where LangChain combined with the Quantive (Gtmhub) MCP Server delivers measurable value.

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

Autonomous research agents: LangChain agents query Quantive (Gtmhub), synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Quantive (Gtmhub) tools with web scrapers, databases, and calculators in a single agent run

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

Quantive (Gtmhub) MCP Tools for LangChain (10)

These 10 tools become available when you connect Quantive (Gtmhub) to LangChain via MCP:

get_key_result

Get details for a specific key result

get_my_profile

Get information about the current authenticated user

get_objective

Get details for a specific OKR objective

list_key_results

List all key results (metrics) in Quantive

list_objectives

List all OKR objectives in Quantive (Gtmhub)

list_sessions

g., Q1, Annual) used to group OKRs. List all planning sessions (timeframes) in Quantive

list_tasks

List tasks associated with OKRs

list_teams

List all organizational teams

list_users

List user profiles in the Quantive account

update_key_result

Update the current value of a key result

Example Prompts for Quantive (Gtmhub) in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Quantive (Gtmhub) immediately.

"What are our main objectives for the current session?"

"Update key result ID 593021 to 75."

"List all teams assigned to our strategic objectives."

Troubleshooting Quantive (Gtmhub) MCP Server with LangChain

Common issues when connecting Quantive (Gtmhub) to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Quantive (Gtmhub) + LangChain FAQ

Common questions about integrating Quantive (Gtmhub) 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.