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The CrateDB MCP Server for natural-language Text-to-SQL and documentation retrieval specializes in CrateDB database clusters.
The Model Context Protocol (MCP) is a protocol that standardizes providing context to language models and AI assistants.
The CrateDB Model Context Protocol (MCP) Server connects AI assistants directly to your CrateDB clusters and the CrateDB knowledge base, enabling seamless interaction through natural language.
It serves as a bridge between AI tools and your analytics database, allowing you to analyze data, the cluster state, troubleshoot issues, and perform operations using conversational prompts.
Experimental: Please note that the CrateDB MCP Server is an experimental feature provided as-is without warranty or support guarantees. Enterprise customers should use this feature at their own discretion.
The CrateDB MCP Server is compatible with AI assistants that support the Model Context Protocol (MCP), either using standard input/output (stdio), server-sent events (SSE), or HTTP Streams (streamable-http).
To use the MCP server, you need a client that supports the protocol. The most notable ones are ChatGPT, Claude, Cline Bot, Cursor, GitHub Copilot, Mistral AI, OpenAI Agents SDK, Windsurf, and others.
The uvx
launcher command is provided by the uv package manager.
The installation docs section includes guidelines on how to
install it on your machine.
Add the following configuration to your AI assistant's settings to enable the CrateDB MCP Server.
- Claude:
claude_desktop_config.json
- Cline:
cline_mcp_settings.json
- Cursor:
~/.cursor/mcp.json
or.cursor/mcp.json
- Roo Code:
mcp_settings.json
or.roo/mcp.json
- Windsurf:
~/.codeium/windsurf/mcp_config.json
{
"mcpServers": {
"cratedb-mcp": {
"command": "uvx",
"args": ["cratedb-mcp", "serve"],
"env": {
"CRATEDB_CLUSTER_URL": "http://localhost:4200/",
"CRATEDB_MCP_TRANSPORT": "stdio"
},
"alwaysAllow": [
"get_health",
"get_table_metadata",
"query_sql",
"get_cratedb_documentation_index",
"fetch_cratedb_docs"
],
"disabled": false
}
}
}
Add an MCP server to your VS Code user settings to enable the MCP server
across all workspaces in your settings.json
file.
{
"mcp": {
"servers": {
"cratedb-mcp": {
"command": "uvx",
"args": ["cratedb-mcp", "serve"],
"env": {
"CRATEDB_CLUSTER_URL": "http://localhost:4200/",
"CRATEDB_MCP_TRANSPORT": "stdio"
}
}
}
},
"chat.mcp.enabled": true
}
Add an MCP server to your VS Code workspace to configure an MCP server for a
specific workspace per .vscode/mcp.json
file. In this case, omit the
top-level mcp
element, and start from servers
instead.
Alternatively, VS Code can automatically detect and reuse MCP servers that you defined in other tools, such as Claude Desktop. See also Automatic discovery of MCP servers.
{
"chat.mcp.discovery.enabled": true
}
Configure extensions
in your ~/.config/goose/config.yaml
.
See also using Goose extensions.
extensions:
cratedb-mcp:
name: CrateDB MCP
type: stdio
cmd: uvx
args:
- cratedb-mcp
- serve
enabled: true
envs:
CRATEDB_CLUSTER_URL: "http://localhost:4200/"
CRATEDB_MCP_TRANSPORT: "stdio"
timeout: 300
Configure mcpServers
in your librechat.yaml
.
See also LibreChat and MCP and LibreChat MCP examples.
mcpServers:
cratedb-mcp:
type: stdio
command: uvx
args:
- cratedb-mcp
- serve
env:
CRATEDB_CLUSTER_URL: "http://localhost:4200/"
CRATEDB_MCP_TRANSPORT: "stdio"
This section includes detailed information about how to configure and operate the CrateDB MCP Server, and to learn about the MCP tools it provides.
Tools are a powerful primitive in the Model Context Protocol (MCP) that enable servers to expose executable functionality to clients. Through tools, LLMs can interact with external systems, perform computations, and take actions in the real world.
The CrateDB MCP Server provides two families of tools.
The Text-to-SQL tools talk to a CrateDB database cluster to inquire database
and table metadata, and table content.
Tool names are: get_health
, get_table_metadata
, query_sql
The documentation server tools looks up guidelines specific to CrateDB topics,
to provide the most accurate information possible.
Relevant information is pulled from https://cratedb.com/docs, curated per
cratedb-outline.yaml through the cratedb-about package.
Tool names are: get_cratedb_documentation_index
, fetch_cratedb_docs
The configuration snippets for AI assistants are using the uvx
launcher
of the uv package manager to start the application after installing it,
like the npx
launcher is doing it for JavaScript and TypeScript applications.
This section uses uv tool install
to install the application persistently.
uv tool install --upgrade cratedb-mcp
Notes:
- We recommend using the uv package manager to install the
cratedb-mcp
package, like many other MCP servers are doing it.{apt,brew,pipx,zypper} install uv
- We recommend using
uv tool install
to install the program "user"-wide into your environment so you can invoke it from anywhere across your terminal sessions or MCP client programs / AI assistants. - If you are unable to use
uv tool install
, you can useuvx cratedb-mcp
to acquire the package and run the application ephemerally.
Configure the CRATEDB_CLUSTER_URL
environment variable to match your CrateDB instance.
For example, when connecting to CrateDB Cloud, use a value like
https://admin:[email protected]:4200/
.
When connecting to CrateDB on localhost, use http://localhost:4200/
.
export CRATEDB_CLUSTER_URL="https://example.aks1.westeurope.azure.cratedb.net:4200"
export CRATEDB_CLUSTER_URL="http://localhost:4200/"
The CRATEDB_MCP_HTTP_TIMEOUT
environment variable (default: 30.0) defines
the timeout for HTTP requests to CrateDB and its documentation resources
in seconds.
The CRATEDB_MCP_DOCS_CACHE_TTL
environment variable (default: 3600) defines
the cache lifetime for documentation resources in seconds.
If you want to prevent agents from modifying data, i.e., permit SELECT
statements
only, it is recommended to create a read-only database user by using "GRANT DQL".
CREATE USER "read-only" WITH (password = 'YOUR_PASSWORD');
GRANT DQL TO "read-only";
Then, include relevant access credentials in the cluster URL.
export CRATEDB_CLUSTER_URL="https://read-only:[email protected]:4200"
The MCP Server also prohibits non-SELECT statements on the application level.
All other operations will raise a PermissionError
exception, unless the
CRATEDB_MCP_PERMIT_ALL_STATEMENTS
environment variable is set to a
truthy value.
Start MCP server with stdio
transport (default).
cratedb-mcp serve --transport=stdio
Start MCP server with sse
transport.
cratedb-mcp serve --transport=sse
Start MCP server with streamable-http
transport.
cratedb-mcp serve --transport=streamable-http
Alternatively, use the CRATEDB_MCP_TRANSPORT
environment variable instead of
the --transport
option.
To connect to the MCP server using any of the available MCP clients, use one of the AI assistant applications, or refer to the programs in the examples folder.
We collected a few example questions that have been tested and validated by the team, so you may also want to try them to get started. Please remember that LLMs can still hallucinate and give incorrect answers.
- Optimize this query: "SELECT * FROM movies WHERE release_date > '2012-12-1' AND revenue"
- Tell me about the health of the cluster
- What is the storage consumption of my tables, give it in a graph.
- How can I format a timestamp column to '2019 Jan 21'?
Please also explore the example questions from another shared collection.
Kudos to the authors of all the many software components and technologies this project is building upon.
The cratedb-mcp
package is an open-source project, and is managed on
GitHub. Contributions of any kind are welcome and appreciated.
To learn how to set up a development sandbox, please refer to the
development documentation.
The software is in the alpha stage, so breaking changes may happen. Version pinning is strongly recommended, especially if you use it as a library.