> ## 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. # Set up ClickHouse MCP server with Ollama > This guide explains how to set up Ollama with a ClickHouse MCP server. > This guide explains how to use the ClickHouse MCP server with Ollama. Ollama is a library for running Large Language Models (LLMs) on your own machine. It has a [wide range of models available](https://ollama.com/library) and is easy to use. You can download Ollama for Mac, Windows, or Linux from the [download page](https://ollama.com/download). Once you run Ollama, it will start a local server in the background that you can use to run models. Alternatively, you can run the server manually by running `ollama serve`. Once installed, you can pull a model down to your machine like this: ```bash theme={null} ollama pull qwen3:8b ``` This will pull the model to your local machine if it isn't present. Once it's downloaded, you can run the model like this: ```bash theme={null} ollama run qwen3:8b ``` Only [models that have tool support](https://ollama.com/search?c=tools) will work with MCP servers. We can list the models that we have downloaded like this: ```bash theme={null} ollama ls ``` ```text theme={null} NAME ID SIZE MODIFIED qwen3:latest 500a1f067a9f 5.2 GB 3 days ago ``` We can use the following command to see more information about the model that we've downloaded: ```bash theme={null} ollama show qwen3 ``` ```text theme={null} Model architecture qwen3 parameters 8.2B context length 40960 embedding length 4096 quantization Q4_K_M Capabilities completion tools Parameters repeat_penalty 1 stop "<|im_start|>" stop "<|im_end|>" temperature 0.6 top_k 20 top_p 0.95 License Apache License Version 2.0, January 2004 ``` We can see from this output that the default qwen3 model has just over 8 billion parameters. At the time of writing (July 2025) there is no native functionality for using Ollama with MCP servers. However, we can use [MCPHost](https://github.com/mark3labs/mcphost) to run Ollama models with MCP servers. MCPHost is a Go application, so you'll need to make sure that you have [Go installed](https://go.dev/doc/install) on your machine. You can then install MCPHost by running the following command: ```bash theme={null} go install github.com/mark3labs/mcphost@latest ``` The binary will be installed under `~/go/bin` so we need to make sure that directory is on our path. We can configure MCP servers with MCPHost in YAML or JSON files. MCPHost will look for config files in your home directory the following order: 1. `.mcphost.yml` or `.mcphost.json` (preferred) 2. `.mcp.yml` or `.mcp.json` (backwards compatibility) It uses a syntax that's similar to that used in the standard MCP configuration file. Here's an example of a ClickHouse MCP server configuration, which we'll save to the `~/.mcphost.json` file: ```json theme={null} { "mcpServers": { "mcp-ch": { "type": "local", "command": ["uv", "run", "--with", "mcp-clickhouse", "--python", "3.10", "mcp-clickhouse" ] } } } ``` The main difference from the standard MCP configuration file is that we need to specify a `type`. The type is used to indicate the transport type used by the MCP server. * `local` → stdio transport * `remote` → streamable transport * `builtin` → inprocess transport We'll also need to configure the following environment variables: ```bash theme={null} export CLICKHOUSE_HOST=sql-clickhouse.clickhouse.com export CLICKHOUSE_USER=demo export CLICKHOUSE_PASSWORD="" ``` In theory, you should be able to provide these variables under the `environment` key in the MCP configuration file, but we've found that this doesn't work. Once you've configured the ClickHouse MCP server, you can run MCPHost by running the following command: ```bash theme={null} mcphost --model ollama:qwen3 ``` Or, if you want to have it use a specific config file: ```bash theme={null} mcphost --model ollama:qwen3 --config ~/.mcphost.json ``` If you don't provide `--model`, MCPHost will look in the environment variables for `ANTHROPIC_API_KEY` and will use the `anthropic:claude-sonnet-4-20250514` model. We should see the following output: ```text theme={null} ┃ ┃ ┃ Model loaded: ollama (qwen3) ┃ ┃ MCPHost System (09:52) ┃ ┃ ┃ ┃ ┃ ┃ Model loaded successfully on GPU ┃ ┃ MCPHost System (09:52) ┃ ┃ ┃ ┃ ┃ ┃ Loaded 3 tools from MCP servers ┃ ┃ MCPHost System (09:52) ┃ ┃ ┃ Enter your prompt (Type /help for commands, Ctrl+C to quit, ESC to cancel generation) ``` We can use the `/servers` command to list the MCP servers: ```text theme={null} ┃ ┃ ┃ ## Configured MCP servers ┃ ┃ ┃ ┃ 1. mcp-ch ┃ ┃ MCPHost System (10:00) ┃ ┃ ``` And `/tools` to list the tools available: ```text theme={null} ┃ ## Available Tools ┃ ┃ ┃ ┃ 1. mcp-ch__list_databases ┃ ┃ 2. mcp-ch__list_tables ┃ ┃ 3. mcp-ch__run_select_query ``` We can then ask the model questions about the databases/tables available in the ClickHouse SQL playground. In our experience when using smaller models (the default qwen3 model has 8 billion parameters), you'll need to be more specific about what you'd like it to do. For example, you'll need to explicitly ask it to list the databases and tables rather than straight away asking it to query a certain table. You can partially eleviate this problem by using a large model (e.g. qwen3:14b), but that will run more slowly on consumer hardware.