> ## Documentation Index
> Fetch the complete documentation index at: https://clickhouse.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Como criar um agente de IA com o framework Microsoft Agent e o servidor MCP do ClickHouse
> Saiba como criar um agente de IA com o framework Microsoft Agent e o servidor MCP do ClickHouse
Neste guia, você aprenderá a criar um agente de IA com o [framework Microsoft Agent](https://github.com/microsoft/agent-framework) que pode interagir com o
[playground SQL do ClickHouse](https://sql.clickhouse.com/) usando o [servidor MCP do ClickHouse](https://github.com/ClickHouse/mcp-clickhouse).
**Notebook de exemplo**
Este exemplo está disponível como um notebook no [repositório de exemplos](https://github.com/ClickHouse/examples/blob/main/ai/mcp/microsoft-agent-framework/microsoft-agent-framework.ipynb).
## Pré-requisitos
* Você precisará ter o Python instalado no seu sistema.
* Você precisará ter o `pip` instalado no seu sistema.
* Você precisará de uma API key da OpenAI
Você pode executar as etapas a seguir no REPL do Python ou por meio de um script.
Instale a biblioteca do framework Microsoft Agent executando os comandos a seguir:
```python theme={null}
pip install -q --upgrade pip
pip install -q agent-framework --pre
pip install -q ipywidgets
```
Em seguida, você precisará fornecer sua chave de API da OpenAI:
```python theme={null}
import os, getpass
os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter OpenAI API Key:")
```
```response title="Response" theme={null}
Enter OpenAI API Key: ········
```
Em seguida, defina as credenciais necessárias para se conectar ao playground do ClickHouse SQL:
```python theme={null}
env = {
"CLICKHOUSE_HOST": "sql-clickhouse.clickhouse.com",
"CLICKHOUSE_PORT": "8443",
"CLICKHOUSE_USER": "demo",
"CLICKHOUSE_PASSWORD": "",
"CLICKHOUSE_SECURE": "true"
}
```
Agora configure o ClickHouse MCP server para apontar para o Playground do ClickHouse SQL
e também inicialize nosso agente e faça uma pergunta a ele:
```python theme={null}
from agent_framework import ChatAgent, MCPStdioTool
from agent_framework.openai import OpenAIResponsesClient
```
```python theme={null}
clickhouse_mcp_server = MCPStdioTool(
name="clickhouse",
command="uv",
args=[
"run",
"--with",
"mcp-clickhouse",
"--python",
"3.10",
"mcp-clickhouse"
],
env=env
)
async with ChatAgent(
chat_client=OpenAIResponsesClient(model_id="gpt-5-mini-2025-08-07"),
name="HousePricesAgent",
instructions="You are a helpful assistant that can help query a ClickHouse database",
tools=clickhouse_mcp_server,
) as agent:
query = "Tell me about UK property prices over the last five years"
print(f"User: {query}")
async for chunk in agent.run_stream(query):
print(chunk.text, end="", flush=True)
print("\n\n")
```
A saída da execução deste script é mostrada abaixo:
```response title="Response" theme={null}
User: Tell me about UK property prices over the last five years
I looked at monthly UK sold-price records in the uk.uk_price_paid_simple_partitioned table for the last five years (toStartOfMonth(date), from Oct 2020 → Aug 2025). Summary and key points:
What I measured
- Metrics: monthly median price, mean price, and transaction count (price paid records).
- Period covered: months starting 2020-10-01 through 2025-08-01 (last five years from today).
High-level findings
- Median price rose from £255,000 (2020-10) to £294,500 (2025-08) — an increase of about +15.4% over five years.
- Equivalent compound annual growth rate (CAGR) for the median ≈ +2.9% per year.
- Mean price fell slightly from about £376,538 (2020-10) to £364,653 (2025-08) — a decline of ≈ −3.2% over five years.
- Mean-price CAGR ≈ −0.6% per year.
- The divergence (median up, mean slightly down) suggests changes in the mix of transactions (fewer very-high-value sales or other compositional effects), since the mean is sensitive to outliers while the median is not.
Notable patterns and events in the data
- Strong rises in 2020–2021 (visible in both median and mean), consistent with the post‑pandemic / stamp‑duty / demand-driven market surge seen in that period.
- Peaks in mean prices around mid‑2022 (mean values ~£440k), then a general softening through 2022–2023 and stabilisation around 2023–2024.
- Some months show large volatility or unusual counts (e.g., June 2021 and June 2021 had very high transaction counts; March 2025 shows a high median but April–May 2025 show lower counts). Recent months (mid‑2025) have much lower transaction counts in the table — this often indicates incomplete reporting for the most recent months and means recent monthly figures should be treated cautiously.
Example datapoints (from the query)
- 2020-10: median £255,000, mean £376,538, transactions 89,125
- 2022-08: mean peak ~£441,209 (median ~£295,000)
- 2025-03: median ~£314,750 (one of the highest medians)
- 2025-08: median £294,500, mean £364,653, transactions 18,815 (low count — likely incomplete)
Caveats
- These are transaction prices (Price Paid dataset) — actual house “values” may differ.
- Mean is sensitive to composition and outliers. Changes in the types of properties sold (e.g., mix of flats vs detached houses, regional mix) will affect mean and median differently.
- Recent months can be incomplete; months with unusually low transaction counts should be treated with caution.
- This is a national aggregate — regional differences can be substantial.
If you want I can:
- Produce a chart of median and mean over time.
- Compare year-on-year or compute CAGR for a different start/end month.
- Break the analysis down by region/county/town, property type (flat, terraced, semi, detached), or by price bands.
- Show a table of top/bottom regions for price growth over the last 5 years.
Which follow-up would you like?
```