Heroku (PaaS) MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Heroku (PaaS) as an MCP tool provider through the 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 Heroku (PaaS). "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Heroku (PaaS)?"
)
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 Heroku (PaaS) MCP Server
Connect your Heroku account to any AI agent and take full control of your cloud-native application management and dyno orchestration through natural conversation.
LlamaIndex agents combine Heroku (PaaS) tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the 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
- App Management — List all hosted applications, create new deployment boundaries, and fetch intricate runtime constraints and framework details directly from your agent
- Dyno Orchestration — List individual containerized dynos, track their status (up, crashed, idle), and selectively reboot specific instances or entire clusters
- Environment & Config — Audit decrypted application environment variables (Config Vars) and retrieve third-party platform add-ons like Postgres or Redis
- Operational Control — Rapidly toggle maintenance mode to block inbound requests during migrations and perform hard reboots on stalled application clusters
- Infrastructure Audit — Identify underlying executing stacks (e.g. heroku-24), regional datacenter placements (US/EU), and total slug size in memory
The Heroku (PaaS) 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.
How to Connect Heroku (PaaS) to LlamaIndex via MCP
Follow these steps to integrate the Heroku (PaaS) 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 10 tools from Heroku (PaaS)
Why Use LlamaIndex with the Heroku (PaaS) MCP Server
LlamaIndex provides unique advantages when paired with Heroku (PaaS) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Heroku (PaaS) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Heroku (PaaS) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Heroku (PaaS), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Heroku (PaaS) tools were called, what data was returned, and how it influenced the final answer
Heroku (PaaS) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Heroku (PaaS) MCP Server delivers measurable value.
Hybrid search: combine Heroku (PaaS) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Heroku (PaaS) 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 Heroku (PaaS) for fresh data
Analytical workflows: chain Heroku (PaaS) queries with LlamaIndex's data connectors to build multi-source analytical reports
Heroku (PaaS) MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Heroku (PaaS) to LlamaIndex via MCP:
create_app
Provision a fresh structural App container on Heroku
delete_app
Traffic routing instantly yields persistent 404/no web-dynos responses. Highly destructive. Permanently wipe an active App from Heroku servers
get_app_info
g. heroku-22, heroku-24). Confirms exact application routing URL mapping, total slug (code) size in memory, and regional datacenter placements (US or EU) verifying global latency strategies. Fetch intricate runtime constraints and framework details of an App
list_addons
Retrieve third-party Platform Add-ons mapping to an App
list_apps
Use this to discover App IDs, web URL designations, and git repository targets required to execute operational commands downstream. List all standard applications actively hosted on Heroku PaaS
list_config_vars
Retrieves highly confidential database tokens `DATABASE_URL`, SendGrid passwords, or OAuth keys. Dump decrypted Application Environment Variables
list_dynos
1, worker.1). Tracks exactly whether the dyno is "up", "crashed", "idle", or "starting" based on the internal slug runner engine's telemetry. List discrete containerized Dynos executing inside an App
restart_all_dynos
Often resolves ephemeral memory-leaks in Node.js or Ruby runtimes stalling standard request processing. Hard reboot all containers tied to an entire Application
restart_specific_dyno
Exceedingly useful for unsticking hung asynchronous queue workers without impacting active web traffic on the primary frontend replicas. Selectively reboot one isolated Dyno instance (e.g. worker.2)
toggle_maintenance_mode
Crucial for orchestrating complex sequential database migrations without encountering corrupted states from active sessions. Rapidly switch an Application's Maintenance Mode switch
Example Prompts for Heroku (PaaS) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Heroku (PaaS) immediately.
"List all my Heroku apps"
"Restart all dynos for 'production-api'"
"What's the current maintenance mode status for the 'staging-web' app?"
Troubleshooting Heroku (PaaS) MCP Server with LlamaIndex
Common issues when connecting Heroku (PaaS) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHeroku (PaaS) + LlamaIndex FAQ
Common questions about integrating Heroku (PaaS) 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 Heroku (PaaS) 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 Heroku (PaaS) to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.