Claid AI MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Claid AI 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 Claid AI. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Claid AI?"
)
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 Claid AI MCP Server
Connect your Claid AI account to any AI agent and take full control of your image enhancement workflows through natural conversation. Transform basic product shots into professional photography instantly.
LlamaIndex agents combine Claid AI tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- AI Enhancement — Apply multiple enhancements like HDR adjustment, white balance, and polishing natively
- Resolution Upscaling — Increase image dimensions using specialized AI models for photos and digital art flawlessly
- Background Logistics — Remove or replace backgrounds with white or custom scenes securely
- Task Oversight — Monitor the status of async processing tasks and retrieve results flawlessly
- Canvas Control — Resize images to specific dimensions with intelligent fit/fill logic flawlessly
- Account Visibility — Retrieve core account information and monitor your AI usage quotas directly within your workspace
The Claid AI MCP Server exposes 8 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 Claid AI to LlamaIndex via MCP
Follow these steps to integrate the Claid AI 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 8 tools from Claid AI
Why Use LlamaIndex with the Claid AI MCP Server
LlamaIndex provides unique advantages when paired with Claid AI through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Claid AI tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Claid AI tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Claid AI, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Claid AI tools were called, what data was returned, and how it influenced the final answer
Claid AI + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Claid AI MCP Server delivers measurable value.
Hybrid search: combine Claid AI real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Claid AI 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 Claid AI for fresh data
Analytical workflows: chain Claid AI queries with LlamaIndex's data connectors to build multi-source analytical reports
Claid AI MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Claid AI to LlamaIndex via MCP:
enhance_image
You can combine multiple operations like upscale, background removal, and HDR adjustment. Apply AI enhancements and edits to an image
get_claid_account_info
Retrieve core account and quota information
get_processing_task_details
Get the status and result of an async image processing task
list_available_ai_operations
List common AI operations supported by the Claid API
list_claid_collections
List image collections in your account
list_claid_webhooks
List configured webhooks for async notifications
remove_image_background
Quickly remove or replace the background of an image
upscale_image_resolution
Increase image resolution using AI models
Example Prompts for Claid AI in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Claid AI immediately.
"Upscale this product photo to high resolution: https://example.com/shoe.jpg"
"Remove the background from this image: https://example.com/model.jpg"
"What is the status of processing task 'task_98765'?"
Troubleshooting Claid AI MCP Server with LlamaIndex
Common issues when connecting Claid AI to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpClaid AI + LlamaIndex FAQ
Common questions about integrating Claid AI 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 Claid AI 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 Claid AI to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.