How to build an AI Agent with mcp-agent and the ClickHouse MCP server

Learn how build an AI Agent with mcp-agent and the ClickHouse MCP server

How to build an AI Agent with CrewAI and the ClickHouse MCP server

In this guide you’ll learn how to build a mcp-agent AI agent that can interact with ClickHouse’s SQL playground using ClickHouse’s MCP server.

Example notebook

This example can be found as a notebook in the examples repository.

Prerequisites

• You’ll need to have Python installed on your system.
• You’ll need to have pip installed on your system.
• You’ll need an OpenAI API key

You can run the following steps either from your Python REPL or via script.

1. Install libraries

   Install the mcp-agent library by running the following commands:

   pip install -q --upgrade pip
   pip install -q mcp-agent openai
   pip install -q ipywidgets
   
2. Setup credentials

   Next, you’ll need to provide your OpenAI API key:

   import os, getpass
   os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter OpenAI API Key:")
   

   Response

   Enter OpenAI API Key: ········
   

   Next, define the credentials needed to connect to the ClickHouse SQL playground:

   env = {
       "CLICKHOUSE_HOST": "sql-clickhouse.clickhouse.com",
       "CLICKHOUSE_PORT": "8443",
       "CLICKHOUSE_USER": "demo",
       "CLICKHOUSE_PASSWORD": "",
       "CLICKHOUSE_SECURE": "true"
   }
   
3. Initialize MCP server and mcp-agent agent

   Now configure the ClickHouse MCP server to point at the ClickHouse SQL playground and also initialize our agent and ask it a question:

   from mcp_agent.app import MCPApp
   from mcp_agent.agents.agent import Agent
   from mcp_agent.workflows.llm.augmented_llm_openai import OpenAIAugmentedLLM
   from mcp_agent.config import Settings, MCPSettings, MCPServerSettings, OpenAISettings
   

   settings = Settings(
       execution_engine="asyncio",
       openai=OpenAISettings(
           default_model="gpt-5-mini-2025-08-07",
       ),
       mcp=MCPSettings(
           servers={
               "clickhouse": MCPServerSettings(
                   command='uv',
                   args=[
                       "run",
                       "--with", "mcp-clickhouse",
                       "--python", "3.10",
                       "mcp-clickhouse"
                   ],
                   env=env
               ),
           }
       ),
   )
   
   app = MCPApp(name="mcp_basic_agent", settings=settings)
   
   async with app.run() as mcp_agent_app:
       logger = mcp_agent_app.logger
       data_agent = Agent(
           name="database-anayst",
           instruction="""You can answer questions with help from a ClickHouse database.""",
           server_names=["clickhouse"],
       )
   
       async with data_agent:
           llm = await data_agent.attach_llm(OpenAIAugmentedLLM)
           result = await llm.generate_str(
               message="Tell me about UK property prices in 2025. Use ClickHouse to work it out."
           )
           
           logger.info(result)
   

   Response

   [10/10/25 11:26:20] INFO     Starting MCP server 'mcp-clickhouse' with transport 'stdio'                                      server.py:1502
   2025-10-10 11:26:20,183 - mcp.server.lowlevel.server - INFO - Processing request of type ListToolsRequest
   2025-10-10 11:26:20,184 - mcp.server.lowlevel.server - INFO - Processing request of type ListPromptsRequest
   2025-10-10 11:26:20,185 - mcp.server.lowlevel.server - INFO - Processing request of type ListResourcesRequest
   [INFO] 2025-10-10T11:26:20 mcp_agent.workflows.llm.augmented_llm_openai.database-anayst - Using reasoning model 'gpt-5-mini-2025-08-07' with
   'medium' reasoning effort
   [INFO] 2025-10-10T11:26:23 mcp_agent.mcp.mcp_aggregator.database-anayst - Requesting tool call
   {
     "data": {
       "progress_action": "Calling Tool",
       "tool_name": "list_databases",
       "server_name": "clickhouse",
       "agent_name": "database-anayst"
     }
   }
   2025-10-10 11:26:23,477 - mcp.server.lowlevel.server - INFO - Processing request of type CallToolRequest
   2025-10-10 11:26:23,479 - mcp-clickhouse - INFO - Listing all databases
   2025-10-10 11:26:23,479 - mcp-clickhouse - INFO - Creating ClickHouse client connection to sql-clickhouse.clickhouse.com:8443 as demo (secure=True, verify=True, connect_timeout=30s, send_receive_timeout=30s)
   2025-10-10 11:26:24,375 - mcp-clickhouse - INFO - Successfully connected to ClickHouse server version 25.8.1.8344
   2025-10-10 11:26:24,551 - mcp-clickhouse - INFO - Found 38 databases
   [INFO] 2025-10-10T11:26:26 mcp_agent.mcp.mcp_aggregator.database-anayst - Requesting tool call
   {
     "data": {
       "progress_action": "Calling Tool",
       "tool_name": "list_tables",
       "server_name": "clickhouse",
       "agent_name": "database-anayst"
     }
   }
   2025-10-10 11:26:26,825 - mcp.server.lowlevel.server - INFO - Processing request of type CallToolRequest
   2025-10-10 11:26:26,832 - mcp-clickhouse - INFO - Listing tables in database 'uk'
   2025-10-10 11:26:26,832 - mcp-clickhouse - INFO - Creating ClickHouse client connection to sql-clickhouse.clickhouse.com:8443 as demo (secure=True, verify=True, connect_timeout=30s, send_receive_timeout=30s)
   2025-10-10 11:26:27,311 - mcp-clickhouse - INFO - Successfully connected to ClickHouse server version 25.8.1.8344
   2025-10-10 11:26:28,738 - mcp-clickhouse - INFO - Found 9 tables
   [INFO] 2025-10-10T11:26:48 mcp_agent.mcp.mcp_aggregator.database-anayst - Requesting tool call
   {
     "data": {
       "progress_action": "Calling Tool",
       "tool_name": "run_select_query",
       "server_name": "clickhouse",
       "agent_name": "database-anayst"
     }
   }
   [INFO] 2025-10-10T11:26:48 mcp_agent.mcp.mcp_aggregator.database-anayst - Requesting tool call
   {
     "data": {
       "progress_action": "Calling Tool",
       "tool_name": "run_select_query",
       "server_name": "clickhouse",
       "agent_name": "database-anayst"
     }
   }
   [INFO] 2025-10-10T11:26:48 mcp_agent.mcp.mcp_aggregator.database-anayst - Requesting tool call
   {
     "data": {
       "progress_action": "Calling Tool",
       "tool_name": "run_select_query",
       "server_name": "clickhouse",
       "agent_name": "database-anayst"
     }
   }
   [INFO] 2025-10-10T11:26:48 mcp_agent.mcp.mcp_aggregator.database-anayst - Requesting tool call
   {
     "data": {
       "progress_action": "Calling Tool",
       "tool_name": "run_select_query",
       "server_name": "clickhouse",
       "agent_name": "database-anayst"
     }
   }
   [INFO] 2025-10-10T11:26:48 mcp_agent.mcp.mcp_aggregator.database-anayst - Requesting tool call
   {
     "data": {
       "progress_action": "Calling Tool",
       "tool_name": "run_select_query",
       "server_name": "clickhouse",
       "agent_name": "database-anayst"
     }
   }
   2025-10-10 11:26:48,366 - mcp.server.lowlevel.server - INFO - Processing request of type CallToolRequest
   2025-10-10 11:26:48,367 - mcp-clickhouse - INFO - Executing SELECT query: SELECT
   count(*) AS transactions,
   avg(price) AS avg_price,
   quantileExact(0.5)(price) AS median_price,
   min(price) AS min_price,
   max(price) AS max_price
   FROM uk.uk_price_paid_simple_partitioned
   WHERE toYear(date)=2025
   2025-10-10 11:26:48,367 - mcp-clickhouse - INFO - Creating ClickHouse client connection to sql-clickhouse.clickhouse.com:8443 as demo (secure=True, verify=True, connect_timeout=30s, send_receive_timeout=30s)
   2025-10-10 11:26:49,262 - mcp-clickhouse - INFO - Successfully connected to ClickHouse server version 25.8.1.8344
   2025-10-10 11:26:49,407 - mcp-clickhouse - INFO - Query returned 1 rows
   2025-10-10 11:26:49,408 - mcp.server.lowlevel.server - INFO - Processing request of type CallToolRequest
   2025-10-10 11:26:49,408 - mcp-clickhouse - INFO - Executing SELECT query: SELECT toMonth(date) AS month, count(*) AS transactions, avg(price) AS avg_price, quantileExact(0.5)(price) AS median_price
   FROM uk.uk_price_paid_simple_partitioned
   WHERE toYear(date)=2025
   GROUP BY month
   ORDER BY month
   2025-10-10 11:26:49,408 - mcp-clickhouse - INFO - Creating ClickHouse client connection to sql-clickhouse.clickhouse.com:8443 as demo (secure=True, verify=True, connect_timeout=30s, send_receive_timeout=30s)
   2025-10-10 11:26:49,857 - mcp-clickhouse - INFO - Successfully connected to ClickHouse server version 25.8.1.8344
   2025-10-10 11:26:50,067 - mcp-clickhouse - INFO - Query returned 8 rows
   2025-10-10 11:26:50,068 - mcp.server.lowlevel.server - INFO - Processing request of type CallToolRequest
   2025-10-10 11:26:50,069 - mcp-clickhouse - INFO - Executing SELECT query: SELECT town, count(*) AS transactions, avg(price) AS avg_price
   FROM uk.uk_price_paid_simple_partitioned
   WHERE toYear(date)=2025
   GROUP BY town
   HAVING transactions >= 50
   ORDER BY avg_price DESC
   LIMIT 10
   2025-10-10 11:26:50,069 - mcp-clickhouse - INFO - Creating ClickHouse client connection to sql-clickhouse.clickhouse.com:8443 as demo (secure=True, verify=True, connect_timeout=30s, send_receive_timeout=30s)
   2025-10-10 11:26:50,594 - mcp-clickhouse - INFO - Successfully connected to ClickHouse server version 25.8.1.8344
   2025-10-10 11:26:50,741 - mcp-clickhouse - INFO - Query returned 10 rows
   2025-10-10 11:26:50,744 - mcp.server.lowlevel.server - INFO - Processing request of type CallToolRequest
   2025-10-10 11:26:50,746 - mcp-clickhouse - INFO - Executing SELECT query: SELECT toYear(date) AS year, count(*) AS transactions, avg(price) AS avg_price, quantileExact(0.5)(price) AS median_price
   FROM uk.uk_price_paid_simple_partitioned
   WHERE toYear(date) IN (2024,2025)
   GROUP BY year
   ORDER BY year
   2025-10-10 11:26:50,747 - mcp-clickhouse - INFO - Creating ClickHouse client connection to sql-clickhouse.clickhouse.com:8443 as demo (secure=True, verify=True, connect_timeout=30s, send_receive_timeout=30s)
   2025-10-10 11:26:51,256 - mcp-clickhouse - INFO - Successfully connected to ClickHouse server version 25.8.1.8344
   2025-10-10 11:26:51,447 - mcp-clickhouse - INFO - Query returned 2 rows
   2025-10-10 11:26:51,449 - mcp.server.lowlevel.server - INFO - Processing request of type CallToolRequest
   2025-10-10 11:26:51,452 - mcp-clickhouse - INFO - Executing SELECT query: SELECT type, count(*) AS transactions, avg(price) AS avg_price, quantileExact(0.5)(price) AS median_price
   FROM uk.uk_price_paid
   WHERE toYear(date)=2025
   GROUP BY type
   ORDER BY avg_price DESC
   2025-10-10 11:26:51,452 - mcp-clickhouse - INFO - Creating ClickHouse client connection to sql-clickhouse.clickhouse.com:8443 as demo (secure=True, verify=True, connect_timeout=30s, send_receive_timeout=30s)
   2025-10-10 11:26:51,952 - mcp-clickhouse - INFO - Successfully connected to ClickHouse server version 25.8.1.8344
   2025-10-10 11:26:52,166 - mcp-clickhouse - INFO - Query returned 5 rows
   [INFO] 2025-10-10T11:27:51 mcp_agent.mcp_basic_agent - Summary (TL;DR)
   - Based on the UK Price Paid tables in ClickHouse, for transactions recorded in 2025 so far there are 376,633 sales with an average price of
   £362,283 and a median price of £281,000. The data appears to include only months Jan–Aug 2025 (so 2025 is incomplete). There are extreme
   outliers (min £100, max £127,700,000) that skew the mean.
   
   What I computed (how)
   I ran aggregations on the uk.price-paid tables in ClickHouse:
   - overall 2025 summary (count, mean, median, min, max) from uk.uk_price_paid_simple_partitioned
   - monthly breakdown for 2025 (transactions, mean, median)
   - top towns in 2025 by average price (towns with >= 50 transactions)
   - year comparison: 2024 vs 2025 (count, mean, median)
   - breakdown by property type for 2025 (counts, avg, median) using uk.uk_price_paid
   
   Key numbers (from the dataset)
   - Overall 2025 (recorded transactions): transactions = 376,633; mean price = £362,282.66; median price = £281,000; min = £100; max =
   £127,700,000.
   - By month (2025): (month, transactions, mean price, median price)
     - Jan: 53,927, mean £386,053, median £285,000
     - Feb: 58,740, mean £371,803, median £285,000
     - Mar: 95,274, mean £377,200, median £315,000
     - Apr: 24,987, mean £331,692, median £235,000
     - May: 39,013, mean £342,380, median £255,000
     - Jun: 41,446, mean £334,667, median £268,500
     - Jul: 44,431, mean £348,293, median £277,500
     - Aug: 18,815, mean £364,653, median £292,999
     (Only months 1–8 are present in the dataset.)
   - Top towns by average price (2025, towns with ≥50 transactions)
     - TRING: 126 txns, avg £1,973,274
     - BUCKHURST HILL: 98 txns, avg £1,441,331
     - ASCOT: 175 txns, avg £1,300,748
     - RADLETT: 69 txns, avg £1,160,217
     - COBHAM: 115 txns, avg £1,035,192
     - EAST MOLESEY, BEACONSFIELD, ESHER, CHALFONT ST GILES, THAMES DITTON are also in the top 10 (all high-average commuter/affluent towns).
   - Year comparison (2024 vs 2025 as recorded)
     - 2024: 859,960 transactions, mean £390,879, median £280,000
     - 2025: 376,633 transactions, mean £362,283, median £281,000
     (2025 counts are much lower because the dataset only includes part of the year.)
   - By property type (2025)
     - detached: 85,362 txns, avg £495,714, median £415,000
     - semi-detached: 107,580 txns, avg £319,922, median £270,000
     - flat: 62,975 txns, avg £298,529, median £227,000
     - terraced: 112,832 txns, avg £286,616, median £227,000
     - other: 7,884 txns, avg £1,087,765 (median £315,000) — note small-group and outlier effect
   
   Important caveats and data quality notes
   - The dataset appears partial for 2025 (only months Jan–Aug present). Any “2025” totals are not full-year figures.
   - Large outliers exist (e.g., max £127.7M, and min £100). These likely include data-entry errors or non-standard records and inflate the
   mean. Median is often a more robust measure here.
   - “other” property-type averages are unstable due to low/heterogeneous counts and outliers.
   - I did not filter by is_new, duration, or other metadata; those filters can change results (for example excluding new-builds or
   leaseholds).
   - The tables are Price Paid-style transaction records (recorded sales) — they do not directly represent asking prices or valuations.
   
   Suggested next steps (I can run these)
   - Clean out obvious outliers (e.g., prices < £10k or > £10M) and recompute averages/medians.
   - Produce regional / county / postcode-area summaries and maps.
   - Compute month-on-month or rolling 3-month median to show trend through 2025.
   - Produce year-on-year (YoY) growth rates by month (e.g., Mar 2025 vs Mar 2024).
   - Forecast for full 2025 using simple extrapolation or time-series modelling (but better after deciding how to handle missing
   months/outliers).
   
   If you want, I can:
   - Re-run the same aggregations after removing extreme outliers and show cleaned results.
   - Produce YoY monthly growth and charts (I can return CSV or JSON aggregates you can chart).
   Which would you like me to do next?
   [INFO] 2025-10-10T11:27:51 mcp_agent.mcp.mcp_aggregator.database-anayst - Last aggregator closing, shutting down all persistent
   connections...
   [INFO] 2025-10-10T11:27:51 mcp_agent.mcp.mcp_connection_manager - Disconnecting all persistent server connections...
   [INFO] 2025-10-10T11:27:51 mcp_agent.mcp.mcp_connection_manager - clickhouse: Requesting shutdown...
   [INFO] 2025-10-10T11:27:51 mcp_agent.mcp.mcp_connection_manager - All persistent server connections signaled to disconnect.
   [INFO] 2025-10-10T11:27:52 mcp_agent.mcp.mcp_aggregator.database-anayst - Connection manager successfully closed and removed from context
   [INFO] 2025-10-10T11:27:52 mcp_agent.mcp_basic_agent - MCPApp cleanup
   {
     "data": {
       "progress_action": "Finished",
       "target": "mcp_basic_agent",
       "agent_name": "mcp_application_loop"
     }
   }