Fellow MCP Server for LangChainGive LangChain instant access to 12 tools to Check Fellow Status, Complete Action Item, Create Action Item, and more
LangChain is the leading Python framework for composable LLM applications. Connect Fellow through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
Ask AI about this App Connector for LangChain
The Fellow app connector for LangChain is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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({
"fellow-alternative": {
"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 Fellow, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 Fellow MCP Server
Connect your Fellow workspace to any AI agent and manage your entire meeting workflow through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Fellow through native MCP adapters. Connect 12 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
- Meetings — List and inspect meetings with titles, participants, dates, and agendas.
- Notes — Access structured meeting notes and AI-generated summaries.
- Action Items — Create, track, and complete action items with assignees and due dates.
- Streams — Browse recurring meeting series and their schedules.
- Users — List all workspace members and their roles.
The Fellow MCP Server exposes 12 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.
All 12 Fellow tools available for LangChain
When LangChain connects to Fellow through Vinkius, your AI agent gets direct access to every tool listed below — spanning meeting-management, collaborative-agendas, action-items, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify Fellow API connectivity
Mark an action item as completed
Optionally link it to a meeting, assign to a user by email, and set a due date. Create a new action item from a meeting
Get details of a specific action item
Get full details of a specific meeting
Get full content of a specific note
Get details of a specific meeting stream
Optionally filter by status: "pending", "completed", or "archived". List action items from meetings
List recent meetings from Fellow
Optionally filter by a specific meeting ID to get notes for that meeting only. List meeting notes
List all meeting streams (recurring series)
List all users in the Fellow workspace
Connect Fellow to LangChain via MCP
Follow these steps to wire Fellow into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the Fellow MCP Server
LangChain provides unique advantages when paired with Fellow through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Fellow 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 Fellow queries for multi-turn workflows
Fellow + LangChain Use Cases
Practical scenarios where LangChain combined with the Fellow MCP Server delivers measurable value.
RAG with live data: combine Fellow tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Fellow, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Fellow tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Fellow tool call, measure latency, and optimize your agent's performance
Example Prompts for Fellow in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Fellow immediately.
"Show me my recent meetings in Fellow."
"Create an action item 'Send proposal to client' and assign it to sarah@team.com with a due date of May 10."
"List all pending action items."
Troubleshooting Fellow MCP Server with LangChain
Common issues when connecting Fellow to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersFellow + LangChain FAQ
Common questions about integrating Fellow MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.