ContentKing 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 ContentKing 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 ContentKing. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in ContentKing?"
)
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 ContentKing MCP Server
Integrate your AI with ContentKing, the real-time SEO auditing and monitoring platform.
LlamaIndex agents combine ContentKing 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
- Site Audits — Review crawled pages and identify active SEO risks or technical errors instantly.
- Change Monitoring — Get summaries of recent alerts or infrastructure changes impacting SEO.
- Metric Retrieval — Fetch health scores and page-level data for your reporting workflows.
The ContentKing 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 ContentKing to LlamaIndex via MCP
Follow these steps to integrate the ContentKing 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 ContentKing
Why Use LlamaIndex with the ContentKing MCP Server
LlamaIndex provides unique advantages when paired with ContentKing through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine ContentKing tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain ContentKing tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query ContentKing, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what ContentKing tools were called, what data was returned, and how it influenced the final answer
ContentKing + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the ContentKing MCP Server delivers measurable value.
Hybrid search: combine ContentKing real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query ContentKing 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 ContentKing for fresh data
Analytical workflows: chain ContentKing queries with LlamaIndex's data connectors to build multi-source analytical reports
ContentKing MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect ContentKing to LlamaIndex via MCP:
get_active_alerts
Get active monitoring alerts for a website
get_issue_details
Get details for a specific SEO issue
get_portfolio_summary
Get a high-level health summary across all websites
get_website_health
Get current health score and status for a website
list_monitored_pages
List monitoring data for pages on a website
list_seo_issues
List SEO issues for a website
list_websites
List all websites monitored in ContentKing
notify_page_update
Notify ContentKing of page updates to trigger re-crawl
notify_sitemap_update
Notify ContentKing that a sitemap has been updated
search_pages_by_url
Search for monitored pages by URL keyword
Example Prompts for ContentKing in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with ContentKing immediately.
"Get the current health score for 'vinkius.com'."
"List all critical alerts for meta tag changes today."
"Give me a high-level summary of the health of all my monitored websites."
Troubleshooting ContentKing MCP Server with LlamaIndex
Common issues when connecting ContentKing to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpContentKing + LlamaIndex FAQ
Common questions about integrating ContentKing 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 ContentKing 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 ContentKing to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.