UserEcho MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Create Support Ticket, Get Ticket Details, List Account Users, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add UserEcho 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 UserEcho app connector for LlamaIndex is a standout in the Collaboration category — giving your AI agent 6 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 UserEcho. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in UserEcho?"
)
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 UserEcho MCP Server
Connect your UserEcho account to any AI agent and simplify how you manage your community feedback, helpdesk tickets, and self-service content through natural conversation.
LlamaIndex agents combine UserEcho tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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
- Helpdesk Management — List all support tickets and retrieve detailed conversation history and status for specific issues.
- Direct Ticketing — Programmatically create new support tickets directly from your agent to accelerate customer assistance.
- Knowledge Base Access — List and query all articles in your help center to verify self-service documentation.
- Forum Oversight — List and monitor feedback and support forums to understand community trends and suggestions.
- User Directory — List account users and team members to manage your support organization structure.
- Issue Tracking — Monitor the progress of client requests and verify resolution times via AI.
The UserEcho MCP Server exposes 6 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 6 UserEcho tools available for LlamaIndex
When LlamaIndex connects to UserEcho through Vinkius, your AI agent gets direct access to every tool listed below — spanning community-feedback, idea-voting, knowledge-base, 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.
Add a new ticket
Get details for a specific ticket
List account users
List UserEcho forums
List knowledge base articles
List helpdesk tickets
Connect UserEcho to LlamaIndex via MCP
Follow these steps to wire UserEcho 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 UserEcho MCP Server
LlamaIndex provides unique advantages when paired with UserEcho through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine UserEcho tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain UserEcho tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query UserEcho, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what UserEcho tools were called, what data was returned, and how it influenced the final answer
UserEcho + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the UserEcho MCP Server delivers measurable value.
Hybrid search: combine UserEcho real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query UserEcho 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 UserEcho for fresh data
Analytical workflows: chain UserEcho queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for UserEcho in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with UserEcho immediately.
"List all active support tickets in my account."
"Show me the details for ticket #88231."
"Create a support ticket: 'API Timeout error' with content 'Receiving 504 errors on the /v1/users endpoint'."
Troubleshooting UserEcho MCP Server with LlamaIndex
Common issues when connecting UserEcho to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpUserEcho + LlamaIndex FAQ
Common questions about integrating UserEcho MCP Server with LlamaIndex.