Jiminny MCP Server for LangChainGive LangChain instant access to 10 tools to Check Jiminny Status, Get Action Items, Get Activity, and more
LangChain is the leading Python framework for composable LLM applications. Connect Jiminny 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 Jiminny app connector for LangChain is a standout in the Artificial Intelligence category — giving your AI agent 10 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({
"jiminny": {
"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 Jiminny, 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 Jiminny MCP Server
Connect your Jiminny account to any AI agent and take full control of your sales conversation intelligence and automated coaching workflows through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Jiminny 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
- Call Portfolio Orchestration — List and manage your entire database of call recordings and transcripts programmatically, retrieving detailed speaker metadata
- Meeting Intelligence Architecture — Programmatically query and monitor meeting insights and key moments to maintain a perfectly coordinated sales audit trail
- Rep Performance Monitoring — Access real-time activity metrics for your sales team and track improvement trends directly through your agent for instant reporting
- Metadata Management — Programmatically retrieve talk-to-listen ratios and filler word counts to maintain a perfectly coordinated coaching record
- Operational Monitoring — Verify account-level API connectivity and monitor call ingestion volume directly through your agent for perfectly coordinated service scaling
The Jiminny 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.
All 10 Jiminny tools available for LangChain
When LangChain connects to Jiminny through Vinkius, your AI agent gets direct access to every tool listed below — spanning conversation-intelligence, sales-coaching, call-recording, 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 Jiminny API connectivity
Get action items from a call
Get activity details
Get aggregate call analytics
Get coaching stats for a user
Get call transcript
Get user details
List all calls and meetings
List all teams
List all team members
Connect Jiminny to LangChain via MCP
Follow these steps to wire Jiminny 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 Jiminny MCP Server
LangChain provides unique advantages when paired with Jiminny through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Jiminny 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 Jiminny queries for multi-turn workflows
Jiminny + LangChain Use Cases
Practical scenarios where LangChain combined with the Jiminny MCP Server delivers measurable value.
RAG with live data: combine Jiminny tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Jiminny, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Jiminny tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Jiminny tool call, measure latency, and optimize your agent's performance
Example Prompts for Jiminny in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Jiminny immediately.
"List all calls recorded today in Jiminny."
"Get the transcript and action items from call ACT-9421."
"Show coaching stats for user USR-201."
Troubleshooting Jiminny MCP Server with LangChain
Common issues when connecting Jiminny to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersJiminny + LangChain FAQ
Common questions about integrating Jiminny 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.