How do I find my Pipeliner Space ID and Service URL?

Log in to Pipeliner, go to **Admin Space** > **API**. There you can find your unique Space ID and the specific API Service URL for your instance.

Can I see opportunities across multiple pipelines?

Yes! Use the `list_pipeliner_opportunities` tool to retrieve a full list of deals. You can then ask the AI agent to filter or group them by pipeline name.

Does this support looking up individual user activities?

Absolutely. Use the `list_pipeliner_activities` tool to retrieve a log of all sales tasks, calls, and meetings recorded in your CRM space.

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

Name: Pipeliner
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 Pipeliner 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({
        "pipeliner": {
            "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 Pipeliner, 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 Pipeliner MCP Server

Connect your Pipeliner CRM space to any AI agent and take full control of your sales ecosystem through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Pipeliner 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

Lead & Opportunity Oversight — List and retrieve detailed metadata for leads and sales opportunities across your workspace.
Sales Pipeline Management — List available pipelines and track the progress of deals through different stages.
Workforce Visibility — List company accounts, business contacts, and team members to maintain a clear view of your stakeholders.
Activity & Task Tracking — Monitor sales activities and assigned tasks to ensure your team stays productive.
Detailed Entity Inspections — Get deep-dive details for any specific lead or opportunity to understand its full history.

The Pipeliner 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 Pipeliner to LangChain via MCP

Follow these steps to integrate the Pipeliner 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 Pipeliner via MCP

Why Use LangChain with the Pipeliner MCP Server

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

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

Pipeliner + LangChain Use Cases

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

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

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

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

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

Pipeliner MCP Tools for LangChain (10)

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

get_pipeliner_lead

Get details for a specific lead

get_pipeliner_opportunity

Get details for a specific opportunity

list_pipeliner_accounts

List all company accounts

list_pipeliner_activities

List sales activities and tasks

list_pipeliner_contacts

List all business contacts

list_pipeliner_leads

List all sales leads

list_pipeliner_opportunities

List all sales opportunities

list_pipeliner_pipelines

List available sales pipelines

list_pipeliner_tasks

List all assigned tasks

list_pipeliner_users

List users in the Pipeliner space

Example Prompts for Pipeliner in LangChain

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

"List all sales opportunities in the 'Enterprise' pipeline."

"Show me the last 5 leads added to Pipeliner."

"What are my sales activities for this week?"

Troubleshooting Pipeliner MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Pipeliner + LangChain FAQ

Common questions about integrating Pipeliner 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.