JobNimbus MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect JobNimbus 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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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({
"jobnimbus": {
"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 JobNimbus, 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 JobNimbus MCP Server
Empower your AI agents with JobNimbus's specialized CRM for contractors. This MCP server allows you to list and retrieve contacts and jobs, manage tasks and workflows, track payments, and view organization users directly through the JobNimbus API. Ideal for automating field service operations and project management.
LangChain's ecosystem of 500+ components combines seamlessly with JobNimbus 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.
The JobNimbus 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 JobNimbus to LangChain via MCP
Follow these steps to integrate the JobNimbus 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 JobNimbus via MCP
Why Use LangChain with the JobNimbus MCP Server
LangChain provides unique advantages when paired with JobNimbus through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine JobNimbus 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 JobNimbus queries for multi-turn workflows
JobNimbus + LangChain Use Cases
Practical scenarios where LangChain combined with the JobNimbus MCP Server delivers measurable value.
RAG with live data: combine JobNimbus tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query JobNimbus, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain JobNimbus tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every JobNimbus tool call, measure latency, and optimize your agent's performance
JobNimbus MCP Tools for LangChain (10)
These 10 tools become available when you connect JobNimbus to LangChain via MCP:
get_contact
Returns addresses, phone numbers, email, and custom fields. Use this for deep intelligence on a customer before an interaction. Retrieves details for a specific contact
get_job
Returns project descriptions, associated contact IDs, and current workflow status. Use this to analyze project specifics or provide an update on a job. Retrieves details for a specific job
list_boards
Useful for navigating the account structure. Lists all configured boards
list_contacts
Returns names, contact types, and IDs. Use this to identify clients or start a search for a specific customer. Lists all contacts in JobNimbus
list_jobs
Includes job titles, status, and IDs. Essential for monitoring project flow and upcoming work. Lists all jobs in JobNimbus
list_payments
Essential for monitoring revenue and project billing status. Lists all recent payments
list_products
Useful for auditing available services and pricing items. Lists all products and services
list_tasks
Returns task descriptions, due dates, and IDs. Use this to help the user manage their daily workload or audit team activities. Lists all tasks
list_users
Useful for identifying sales reps or project managers. Lists all users in the organization
list_workflows
Useful for understanding the steps in the company's business processes. Lists all configured workflows
Example Prompts for JobNimbus in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with JobNimbus immediately.
"List all active contacts in JobNimbus."
"Show me the latest jobs created."
"Check the status of my active tasks."
Troubleshooting JobNimbus MCP Server with LangChain
Common issues when connecting JobNimbus to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersJobNimbus + LangChain FAQ
Common questions about integrating JobNimbus 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.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect JobNimbus with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect JobNimbus to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.