Innform MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Innform through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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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({
"innform": {
"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 Innform, 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 Innform MCP Server
Empower your AI agents to manage your training platform with Innform. This MCP server allows you to list learners, track course completion, manage learning pathways, and view results directly through the Innform API. Ideal for automating corporate training and employee development.
LangChain's ecosystem of 500+ components combines seamlessly with Innform 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 Innform 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 Innform to LangChain via MCP
Follow these steps to integrate the Innform 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 Innform via MCP
Why Use LangChain with the Innform MCP Server
LangChain provides unique advantages when paired with Innform through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Innform 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 Innform queries for multi-turn workflows
Innform + LangChain Use Cases
Practical scenarios where LangChain combined with the Innform MCP Server delivers measurable value.
RAG with live data: combine Innform tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Innform, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Innform tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Innform tool call, measure latency, and optimize your agent's performance
Innform MCP Tools for LangChain (10)
These 10 tools become available when you connect Innform to LangChain via MCP:
get_learner
Retrieves details for a specific learner
get_me
Gets current authenticated user info
list_courses
Lists all courses
list_departments
Lists all departments
list_learners
Lists all learners in Innform
list_locations
Lists all organization locations
list_modules
Lists all training modules
list_pathways
Lists all learning pathways
list_results
Lists learner assessment and course results
list_tags
Lists all defined tags
Example Prompts for Innform in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Innform immediately.
"List all active learners in my Innform account."
"Show me the results for 'Cybersecurity Awareness' course."
"Check for any new learning pathways."
Troubleshooting Innform MCP Server with LangChain
Common issues when connecting Innform to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersInnform + LangChain FAQ
Common questions about integrating Innform 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 Innform 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 Innform to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.