Bring Churn Reduction
to LlamaIndex
Learn how to connect Upzelo to LlamaIndex and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Upzelo MCP Server?
Connect your Upzelo churn management account to any AI agent and simplify how you retain customers and manage subscription lifecycles through natural conversation.
What you can do
- Customer Management — List and search customer records, and update profile data for better segmentation and targeting.
- Retention Flows — List available flows and manually trigger retention sequences for customers at risk of cancelling.
- Subscription Tracking — Query all tracked subscriptions and update statuses or trial details programmatically.
- Flow Monitoring — Check the real-time status and outcomes of active flow sessions to verify retention success.
- External ID Sync — Link your internal system identifiers to Upzelo customer records for seamless integration.
How it works
1. Subscribe to this server
2. Enter your Upzelo App ID and API Key (found in your developer settings)
3. Start managing your retention strategy from Claude, Cursor, or any MCP client
Who is this for?
- Customer Success Managers — quickly trigger retention flows and check customer health via simple AI commands.
- Product Operations — monitor subscription statuses and sync customer data directly from the workspace.
- Business Growth Teams — get instant insights into flow performance and active retention sessions.
Built-in capabilities (10)
Get details for a specific customer
Get details for a specific flow
Check the status of a flow session
Get details for a specific subscription
List all customers in Upzelo
List all retention flows
List all subscriptions
Used for segmentation and targeting. Create or update a customer record
Initialize a flow for a customer
Update subscription attributes
Why LlamaIndex?
LlamaIndex agents combine Upzelo 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.
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Data-first architecture: LlamaIndex agents combine Upzelo tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Upzelo tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Upzelo, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Upzelo tools were called, what data was returned, and how it influenced the final answer
Upzelo in LlamaIndex
Upzelo and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Upzelo to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Upzelo in LlamaIndex
The Upzelo 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. All 10 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Upzelo for LlamaIndex
Every tool call from LlamaIndex to the Upzelo MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I manually start a retention flow for a customer via AI?
Yes! Use the start_flow tool and provide the Flow ID, Customer ID, and Subscription ID. This will initialize the retention experience for that user immediately.
How do I see if a customer successfully stayed after a flow?
Run the get_flow_session query with the specific Session ID. It will return the outcome and status of the retention attempt.
Is it possible to update a subscription's status via AI?
Absolutely. Use the update_subscription tool by providing the Subscription ID and the new status to synchronize data between your systems and Upzelo.
How does LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query Upzelo tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp