Compatible with every major AI agent and IDE
What is the HiFlow MCP Server?
The HiFlow MCP server bridges your AI agent with your enterprise workflows. Trigger processes, approve pending steps, and query real-time process states through a seamless conversational interface.
Built-in capabilities (12)
Create a new customer
Retrieve activity dashboard information
Retrieve details for a specific customer
Retrieve details for a specific estimate
Retrieve details for a specific invoice
Retrieve details for a specific job
Retrieve information about the current user
List all customers
List all estimates (quotes)
List all invoices
List all jobs/projects
List all timesheet entries
Why LlamaIndex?
LlamaIndex agents combine HiFlow 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.
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Data-first architecture: LlamaIndex agents combine HiFlow tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain HiFlow tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query HiFlow, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what HiFlow tools were called, what data was returned, and how it influenced the final answer
HiFlow in LlamaIndex
HiFlow and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect HiFlow 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 | 4,000+ 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 HiFlow in LlamaIndex
The HiFlow 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 12 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
HiFlow for LlamaIndex
Every tool call from LlamaIndex to the HiFlow MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I start a new workflow from the AI?
Yes, you can trigger new workflow instances by specifying the process ID and required variables.
How do I check pending tasks?
Ask the agent to 'List my pending approvals', and it will retrieve the queue of tasks requiring your attention.
Is it possible to approve a task directly in the chat?
Yes! Provide the task ID and tell the agent to mark it as approved or rejected.
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 HiFlow 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
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