GatherUp MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add GatherUp as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
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 GatherUp. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in GatherUp?"
)
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 GatherUp MCP Server
Connect your GatherUp account to any AI agent to automate your review management and customer feedback workflows through the Model Context Protocol (MCP). GatherUp is a powerful platform that helps businesses monitor reputation, collect 1st-party feedback, and showcase 3rd-party reviews from sites like Google and Facebook. This MCP server enables you to track review streams, reply to customers, and trigger automated review requests directly through natural conversation.
LlamaIndex agents combine GatherUp tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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.
Key Features
- Business Unit Oversight — List all business locations and retrieve high-level configuration metadata for each unit.
- Feedback Management — Access and retrieve first-party feedback left directly by customers via your GatherUp surveys.
- Online Review Tracking — Monitor third-party reviews from Google, Facebook, Yelp, and more in a centralized feed.
- Real-time Interaction — Send replies to both internal feedback and supported external reviews directly from your chat interface.
- Review Request Automation — Trigger new review invites (email/SMS) to specific customers to boost your reputation.
- Contact Management — Add and sync customer profiles to specific business locations programmatically.
- Reputation Metrics — Fetch high-level statistics and sentiment analysis for any business location instantly.
- API Health Monitoring — Verify your connection to the GatherUp v2 API environment seamlessly.
The GatherUp MCP Server exposes 12 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.
How to Connect GatherUp to LlamaIndex via MCP
Follow these steps to integrate the GatherUp MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 12 tools from GatherUp
Why Use LlamaIndex with the GatherUp MCP Server
LlamaIndex provides unique advantages when paired with GatherUp through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine GatherUp tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain GatherUp tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query GatherUp, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what GatherUp tools were called, what data was returned, and how it influenced the final answer
GatherUp + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the GatherUp MCP Server delivers measurable value.
Hybrid search: combine GatherUp real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query GatherUp 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 GatherUp for fresh data
Analytical workflows: chain GatherUp queries with LlamaIndex's data connectors to build multi-source analytical reports
GatherUp MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect GatherUp to LlamaIndex via MCP:
add_new_customer
Sync a customer
get_account_info
Get user identity
get_review_metrics
Get location stats
list_business_locations
List business units
list_customer_contacts
List customers
list_internal_feedback
List direct feedback
list_online_reviews
List external reviews
reply_to_feedback
Reply to internal feedback
reply_to_online_review
g. Google or Facebook). Reply to external review
search_all_reviews
Search all feedback
send_review_invite
Request a review
verify_api_connection
Check connection
Example Prompts for GatherUp in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with GatherUp immediately.
"List all my business locations in GatherUp."
"Show me the 5 most recent Google reviews for 'Downtown Cafe' (ID: biz_123)."
"Send a review request to customer 'John Doe' (ID: cust_987)."
Troubleshooting GatherUp MCP Server with LlamaIndex
Common issues when connecting GatherUp to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGatherUp + LlamaIndex FAQ
Common questions about integrating GatherUp MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect GatherUp 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 GatherUp to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.