ClickHouse (Vector Search) MCP Server for OpenAI Agents SDK 7 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect ClickHouse (Vector Search) through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="ClickHouse (Vector Search) Assistant",
instructions=(
"You help users interact with ClickHouse (Vector Search). "
"You have access to 7 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from ClickHouse (Vector Search)"
)
print(result.final_output)
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 ClickHouse (Vector Search) MCP Server
Connect your ClickHouse cluster to any AI agent and take full control of your analytical and vector data through natural conversation.
The OpenAI Agents SDK auto-discovers all 7 tools from ClickHouse (Vector Search) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries ClickHouse (Vector Search), another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Schema Management — List databases and tables, and inspect deep column schemas including specialized Array(Float32) vector types
- SQL Execution — Push arbitrary DML, DDL, or SELECT queries to your cluster to manage data and generate real-time reports
- Vector Search — Identify mathematical distance traces using cosineDistance or L2Distance metrics for high-dimensional semantic search
- Cluster Monitoring — Extract internal structural states, row counts, and compression ratios to audit cluster health
- Capability Auditing — Check instance versions and binary limits to identify exact capability branches like HNSW support
The ClickHouse (Vector Search) MCP Server exposes 7 tools through the Vinkius. Connect it to OpenAI Agents SDK 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 ClickHouse (Vector Search) to OpenAI Agents SDK via MCP
Follow these steps to integrate the ClickHouse (Vector Search) MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 7 tools from ClickHouse (Vector Search)
Why Use OpenAI Agents SDK with the ClickHouse (Vector Search) MCP Server
OpenAI Agents SDK provides unique advantages when paired with ClickHouse (Vector Search) through the Model Context Protocol.
Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
ClickHouse (Vector Search) + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the ClickHouse (Vector Search) MCP Server delivers measurable value.
Automated workflows: build agents that query ClickHouse (Vector Search), process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries ClickHouse (Vector Search), another analyzes results, a third generates reports
Data enrichment pipelines: stream data through ClickHouse (Vector Search) tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query ClickHouse (Vector Search) to resolve tickets, look up records, and update statuses without human intervention
ClickHouse (Vector Search) MCP Tools for OpenAI Agents SDK (7)
These 7 tools become available when you connect ClickHouse (Vector Search) to OpenAI Agents SDK via MCP:
describe_table
Perform structural extraction of properties driving active column schemas
execute_sql
Provision a highly-available SQL execution pushing arbitrary arbitrary DML/DDL or SELECTs
get_table_stats
Extracts explicitly attached internal structural states pulling cluster health
get_version
g. HNSW support). Identify precise active cluster limits spanning the execution runtime
list_databases
Identify bounded logical arrays managing top-level ClickHouse schemas
list_tables
Retrieve the exact structural matching verifying table limits inside a database
vector_search
Identify explicit mathematical distance traces routing Vector Embeddings
Example Prompts for ClickHouse (Vector Search) in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with ClickHouse (Vector Search) immediately.
"List all databases in my ClickHouse cluster"
"Find the top 5 most similar records in table 'embeddings' using this vector: [0.1, 0.5, -0.2]"
"Get table stats for 'analytics_prod.sales_data'"
Troubleshooting ClickHouse (Vector Search) MCP Server with OpenAI Agents SDK
Common issues when connecting ClickHouse (Vector Search) to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
ClickHouse (Vector Search) + OpenAI Agents SDK FAQ
Common questions about integrating ClickHouse (Vector Search) MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect ClickHouse (Vector Search) 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 ClickHouse (Vector Search) to OpenAI Agents SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.