Can I check which users belong to a specific collaboration space?

Yes. The `get_space_details` tool allows your AI agent to retrieve the membership count and configuration for any specific space ID, helping you monitor team alignment directly through chat.

How do I see the contact details for a colleague using chat?

You can use the `get_employee_profile` tool. Simply provide the unique employee ID, and your agent will return their full profile details, including email, job title, and department information.

Can I post an announcement to the global activity feed via chat?

Absolutely. Use the `create_social_post` tool and provide your update text. If you don't specify a space ID, the post will be shared to the main company activity feed, making it visible to all users.

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

Name: Workvivo
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 Workvivo through the 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({
        "workvivo": {
            "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 Workvivo, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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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 Workvivo MCP Server

Connect your Workvivo account to any AI agent and manage your employee experience infrastructure through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Workvivo through native MCP adapters. Connect 10 tools via the 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

Social Feed — Browse the company activity feed, retrieve full details for specific posts (likes, comments), and share new updates instantly
Employee Directory — List all registered employees and retrieve comprehensive profile details including contact info and job titles
Collaboration Spaces — Browse interest groups and departmental spaces, retrieve membership counts, and post updates to specific spaces
Company Events — Monitor the company calendar, retrieve details for upcoming events including location and start times
Content Insights — Quickly find unique post, employee, space, and event IDs required for automated internal communication workflows
Team Engagement — Analyze activity levels and browse social interactions across the platform directly from your agent
Data Integrity — Safely delete unfinalized or obsolete social posts through simple chat commands

The Workvivo 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 Workvivo to LangChain via MCP

Follow these steps to integrate the Workvivo 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 Workvivo via MCP

Why Use LangChain with the Workvivo MCP Server

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

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

Workvivo + LangChain Use Cases

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

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

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

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

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

Workvivo MCP Tools for LangChain (10)

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

create_social_post

Provide the text content and an optional space ID. Creates a new post on the Workvivo activity feed

delete_social_post

This action is irreversible. Permanently deletes a post from Workvivo

get_employee_profile

Retrieves profile details for a specific employee

get_event_details

Retrieves details for a specific calendar event

get_post_details

Retrieves details for a specific social post

get_space_details

Retrieves details for a specific collaboration space

list_collaboration_spaces

Lists collaboration spaces (groups) in Workvivo

list_company_events

Lists upcoming events scheduled in Workvivo

list_employees

Lists employees registered in the Workvivo directory

list_workvivo_posts

Lists social posts and activity on the Workvivo platform

Example Prompts for Workvivo in LangChain

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

"List the last 5 posts on the company feed."

"Find the profile for employee ID 'emp-123'."

"What are the details for the 'Town Hall' event today?"

Troubleshooting Workvivo MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Workvivo + LangChain FAQ

Common questions about integrating Workvivo 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.