Roboflow MCP Server for LlamaIndexGive LlamaIndex instant access to 29 tools to Add Projects To Folder, Auto Label, Cancel Training, and more
GDPR Free for SubscribersLlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Roboflow 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 for LlamaIndex
The Roboflow MCP Server for LlamaIndex is a standout in the Developer Tools category — giving your AI agent 29 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport 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 Roboflow. "
"You have 29 tools available."
),
)
response = await agent.run(
"What tools are available in Roboflow?"
)
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 Roboflow MCP Server
Connect Roboflow to your AI agent to streamline your computer vision pipeline. From dataset management to model training and inference, handle your entire CV lifecycle through natural language.
LlamaIndex agents combine Roboflow tool responses with indexed documents for comprehensive, grounded answers. Connect 29 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
- Workspace & Project Management — List projects, create new ones, or fork from Roboflow Universe to jumpstart your development.
- Dataset Operations — Upload images (via URL or Base64), manage versions, and download datasets in various formats like COCO or YOLO.
- Model Training — Start training runs, monitor results, and retrieve precise performance metrics (mAP, precision, recall) for any version.
- Image Search — Search and filter images within your workspace to audit your data and improve model accuracy.
- Inference & Results — Run inference on images and retrieve results to verify model behavior in real-time.
The Roboflow MCP Server exposes 29 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 29 Roboflow tools available for LlamaIndex
When LlamaIndex connects to Roboflow through Vinkius, your AI agent gets direct access to every tool listed below — spanning computer-vision, dataset-management, model-training, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Add projects to folder on Roboflow
Add projects to a folder (Enterprise)
Auto label on Roboflow
Start an auto-labeling job using foundation models
Cancel training on Roboflow
Cancel an active training job
Create annotation job on Roboflow
Assign a batch of images to a labeler and reviewer
Create folder on Roboflow
Create a project folder (Enterprise)
Create project on Roboflow
Create a new project in a workspace
Delete images on Roboflow
Delete multiple images from a project
Delete project on Roboflow
Delete a project or version (moves to Trash)
Download dataset on Roboflow
Retrieve a download link for a zipped dataset in a specific format
Fork universe project on Roboflow
Fork a public project from Roboflow Universe
Get async task on Roboflow
Track long-running operations like forking or large exports
Get dataset health on Roboflow
Check dataset health (class distribution, missing annotations, etc)
Get image on Roboflow
Get details for a specific image
Get project on Roboflow
Get project details, metadata, and versions
Get root on Roboflow
Verify authentication and retrieve default workspace
Get training results on Roboflow
Retrieve metrics and status for a version training run
Get version on Roboflow
Retrieve metadata for a specific dataset version
List folders on Roboflow
List project folders in a workspace (Enterprise)
List trash on Roboflow
List items in the workspace trash
List workspace projects on Roboflow
List information about a workspace and its projects
Manage image tags on Roboflow
Add, remove, or set tags on an image
Restore trash on Roboflow
Restore an item from the trash
Run inference on Roboflow
Run inference on an image using hosted models
Search project images on Roboflow
Search and filter images within a specific project
Search workspace images on Roboflow
Search and filter images within a workspace
Start training on Roboflow
Start training a model on a dataset version
Stop training on Roboflow
Early stop an active training job
Upload annotation on Roboflow
Attach an annotation file to an existing image
Upload image on Roboflow
Upload an image to a project
Connect Roboflow to LlamaIndex via MCP
Follow these steps to wire Roboflow into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind 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 Roboflow MCP Server
LlamaIndex provides unique advantages when paired with Roboflow through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Roboflow tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Roboflow tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Roboflow, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Roboflow tools were called, what data was returned, and how it influenced the final answer
Roboflow + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Roboflow MCP Server delivers measurable value.
Hybrid search: combine Roboflow real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Roboflow 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 Roboflow for fresh data
Analytical workflows: chain Roboflow queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Roboflow in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Roboflow immediately.
"List all projects in my Roboflow workspace 'industrial-safety'."
"Upload this image URL to the 'Hard Hat Detection' project in workspace 'industrial-safety'."
"Show me the training metrics for version 5 of the 'Forklift Tracking' project."
Troubleshooting Roboflow MCP Server with LlamaIndex
Common issues when connecting Roboflow to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpRoboflow + LlamaIndex FAQ
Common questions about integrating Roboflow 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?
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