Transloadit MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Cancel Assembly, Create Assembly, Create Template, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Transloadit 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 App Connector for LlamaIndex
The Transloadit app connector for LlamaIndex is a standout in the Developer Tools category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Transloadit. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Transloadit?"
)
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 Transloadit MCP Server
The Transloadit MCP server allows your AI agent to orchestrate complex file processing pipelines. Trigger encodings, convert documents, resize images, and monitor assembly statuses right from your conversation.
LlamaIndex agents combine Transloadit 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.
The Transloadit 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.
All 12 Transloadit tools available for LlamaIndex
When LlamaIndex connects to Transloadit through Vinkius, your AI agent gets direct access to every tool listed below — spanning file-processing, media-encoding, file-upload, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Stop a currently running assembly
Start a new file processing assembly
Create a new processing template
Permanently remove a template
Retrieve status and results for a specific assembly
Retrieve billing information for a specific month
Check API connectivity and get account context
Retrieve details for a specific template
List all file processing assemblies
List all reusable processing templates
Re-run a completed assembly
Update an existing template
Connect Transloadit to LlamaIndex via MCP
Follow these steps to wire Transloadit into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Transloadit MCP Server
LlamaIndex provides unique advantages when paired with Transloadit through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Transloadit tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Transloadit tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Transloadit, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Transloadit tools were called, what data was returned, and how it influenced the final answer
Transloadit + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Transloadit MCP Server delivers measurable value.
Hybrid search: combine Transloadit real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Transloadit 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 Transloadit for fresh data
Analytical workflows: chain Transloadit queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Transloadit in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Transloadit immediately.
"List all available Transloadit templates."
"Check the status of Assembly ID 88392."
"Cancel the processing for Assembly ID 99120."
Troubleshooting Transloadit MCP Server with LlamaIndex
Common issues when connecting Transloadit to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTransloadit + LlamaIndex FAQ
Common questions about integrating Transloadit MCP Server with LlamaIndex.