Keepcon MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Keepcon 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 Keepcon. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Keepcon?"
)
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 Keepcon MCP Server
Empower your AI agents to moderate user-generated content using Keepcon. This MCP server enables seamless integration with Keepcon's semantic moderation engine for both real-time and batch processing.
LlamaIndex agents combine Keepcon tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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
- Real-time Moderation — Submit text for immediate moderation decisions (approve/reject) and category tagging
- Batch Processing — Import large volumes of content for asynchronous moderation and retrieve results in bulk
- Result Management — Export pending moderation decisions and acknowledge processed results to maintain a clean queue
- Feedback Loop — Submit feedback on moderation decisions to improve the accuracy of the semantic engine
- Profile Insight — List and query user profiles associated with moderated content
The Keepcon MCP Server exposes 9 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 Keepcon to LlamaIndex via MCP
Follow these steps to integrate the Keepcon 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 9 tools from Keepcon
Why Use LlamaIndex with the Keepcon MCP Server
LlamaIndex provides unique advantages when paired with Keepcon through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Keepcon tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Keepcon tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Keepcon, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Keepcon tools were called, what data was returned, and how it influenced the final answer
Keepcon + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Keepcon MCP Server delivers measurable value.
Hybrid search: combine Keepcon real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Keepcon 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 Keepcon for fresh data
Analytical workflows: chain Keepcon queries with LlamaIndex's data connectors to build multi-source analytical reports
Keepcon MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect Keepcon to LlamaIndex via MCP:
acknowledge_results
Acknowledge receipt of results
export_results
Retrieve batch moderation results
get_profile
Get a specific user profile by Keepcon ID
get_profile_by_social_id
g., twitter, facebook) and the network-specific user ID. Get a user profile by social network ID
import_batch
Returns an import ID. Submit content for batch moderation
list_profiles
List user profiles
moderate_content
Returns the decision (approve/reject) and tags. Moderates content in real-time
search_profiles
Search profiles with filters
submit_feedback
g., false positives) to improve the semantic engine. Submit moderation feedback
Example Prompts for Keepcon in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Keepcon immediately.
"Moderate this text in the 'forum' context: 'This user is being very aggressive!'"
"Export pending moderation results for the 'chat' context."
"List all user profiles in my Keepcon account."
Troubleshooting Keepcon MCP Server with LlamaIndex
Common issues when connecting Keepcon to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKeepcon + LlamaIndex FAQ
Common questions about integrating Keepcon 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 Keepcon 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 Keepcon to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.