Jiminny MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Check Jiminny Status, Get Action Items, Get Activity, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Jiminny as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Jiminny app connector for LlamaIndex 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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Jiminny. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Jiminny?"
)
print(response)
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.
LlamaIndex agents combine Jiminny tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex
When LlamaIndex 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 LlamaIndex via MCP
Follow these steps to wire Jiminny into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Jiminny MCP Server
LlamaIndex provides unique advantages when paired with Jiminny through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Jiminny tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Jiminny tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Jiminny, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Jiminny tools were called, what data was returned, and how it influenced the final answer
Jiminny + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Jiminny MCP Server delivers measurable value.
Hybrid search: combine Jiminny real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Jiminny to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Jiminny for fresh data
Analytical workflows: chain Jiminny queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Jiminny in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Jiminny to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpJiminny + LlamaIndex FAQ
Common questions about integrating Jiminny MCP Server with LlamaIndex.