Dokku 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 Dokku 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 MCP SERVER
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 Dokku. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Dokku?"
)
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 Dokku MCP Server
Connect your Dokku instance to any AI agent and take full control of your self-hosted PaaS and container orchestration through natural conversation.
LlamaIndex agents combine Dokku 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.
What you can do
- Application Lifecycle — List all managed apps and retrieve the overarching directory of deployments on your own infrastructure bypassing standard PaaS fees
- Provisioning & Deallocation — Barely instantiate new application repositories or irreversibly dismantle all bound containers and DNS routing records
- Environment Auditing — Retrieve the exact
.envdictionary bound dynamically via the config plugin to observe runtime inputs and SQL credentials - Configuration Mutation — Inject or remove sensitive environment variables securely, triggering rolling app deployments natively across your cluster
- Process Scaling — Manipulate explicit replica counts dynamically, determining whether web or worker containers spool up to meet demand
- Live Log Streaming — Pull precise system execution tails to investigate explicit request stack traces and crashing node backtraces without SSH
- One-off Executions — Launch raw commands inside ephemeral isolated containers for maintenance tasks like DB migrations or custom scripts
The Dokku 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 Dokku to LlamaIndex via MCP
Follow these steps to integrate the Dokku 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 Dokku
Why Use LlamaIndex with the Dokku MCP Server
LlamaIndex provides unique advantages when paired with Dokku through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Dokku tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Dokku tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Dokku, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Dokku tools were called, what data was returned, and how it influenced the final answer
Dokku + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Dokku MCP Server delivers measurable value.
Hybrid search: combine Dokku real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Dokku 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 Dokku for fresh data
Analytical workflows: chain Dokku queries with LlamaIndex's data connectors to build multi-source analytical reports
Dokku MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Dokku to LlamaIndex via MCP:
create_app
Performs the structural network allocations setting up reverse-proxy hooks (Nginx/Traefik) preceding the actual codebase transfer. Provision a root App boundary wrapper on the Dokku VM
destroy_app
Instantly shuts down bound running docker containers orchestrating web/worker traffic, detaches volumes seamlessly, and removes explicit DNS routing records from the local VHOST mappings. Deallocate an App and dismantle all bound containers completely
get_logs
Bypasses SSH to investigate explicit request stack traces, crashing node backtraces, or slow SQL queries happening inside the closed containers. Stream Dokku Application Docker stdout and stderr logs
list_apps
Determines exactly which Docker containers are orchestrated internally by Dokku Core scaling plugins. List self-hosted Git-push Apps deployed via Dokku
list_config
env` or `ENV` dictionary bound dynamically via the `dokku config` plugin. Used strictly to observe runtime inputs (SQL credentials, external REST API tokens, Node_ENV bindings) governing app execution. Extract internal Environment variables loaded into the App
ps_restart
Dokku tears down old running docker processes spanning the App UUID, allocating updated dynamic ports tied via standard proxies (Nginx), ensuring zero downtime deploys if multiple replicas are alive. Bounce the application container dynamically
ps_scale
Determines whether the "web" container spins zero replicas (suspension), or if "worker" background tasks spool up to 10 endpoints. Scale structural internal application containers
run_command
Boots a brand new isolated Docker container cloning the production image layers for a single execution cycle. Useful for running `rake db:migrate`, `npm run script` safely disconnected from web traffic. Launch a raw one-off command inside an ephemeral container
set_config
Triggers a mandatory rolling app deployment unless the `--no-restart` daemon flag applies natively to the process. Critical for updating expired API auth tokens. Inject Environment Variables into a running Dokku Application
unset_config
Immediately triggers the executing Docker cluster to orchestrate a rapid replacement cycle to strip out the revoked value. Removes stale credentials safely. Remove sensitive Environment Variables disrupting App config
Example Prompts for Dokku in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Dokku immediately.
"List all apps on my Dokku host"
"Scale the 'web' process of app 'api-server' to 3 replicas"
"Get the last 50 lines of logs for 'frontend-web'"
Troubleshooting Dokku MCP Server with LlamaIndex
Common issues when connecting Dokku to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDokku + LlamaIndex FAQ
Common questions about integrating Dokku 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 Dokku 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 Dokku to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.