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MCP: Add first wave of material, mostly indexing existing others
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docs/integrate/index.md

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etl/index
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mcp/index
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metrics/index
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docs/integrate/mcp/community.md

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# MCP Community Servers
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This section introduces popular community-run Model Context Protocol servers
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for PostgreSQL and CrateDB.
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::::{grid} 1
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:gutter: 2
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:::{grid-item-card} {material-outlined}`image_search;2em` MCP Server landscape
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:link: ctk:query/mcp/landscape
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:link-type: doc
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:link-alt: MCP Server landscape
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:class-footer: text-smaller
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An overview of the MCP server landscape, focusing on the most popular servers
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that connect to both PostgreSQL and CrateDB.
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+++
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The document includes detailed MCP API capabilities about all of them,
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regarding available prompts, resources, and tools.
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:::
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:::{grid-item-card} {material-outlined}`settings;2em` Configure
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:link: ctk:query/mcp/server
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:link-type: doc
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:link-alt: MCP Server configuration
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:class-footer: text-smaller
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Guidelines for configuring popular MCP servers that connect
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to both PostgreSQL and CrateDB.
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+++
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The document includes detailed configuration snippets and enumerates
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available configuration options.
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:::
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:::{grid-item-card} {material-outlined}`not_started;2em` Examples
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:link: https://github.com/crate/cratedb-examples/tree/main/framework/mcp
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:link-type: url
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:link-alt: Community MCP Server examples
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:class-footer: text-smaller
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Ready-to-run example programs using community MCP Servers.
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:::
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::::

docs/integrate/mcp/cratedb-mcp.md

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# CrateDB MCP Server
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:::{rubric} About
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:::
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The CrateDB MCP Server for natural-language Text-to-SQL and documentation
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retrieval specializes in CrateDB database clusters.
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The Model Context Protocol ([MCP]) is a protocol that standardizes providing
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context to language models and AI assistants.
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:::{rubric} Introduction
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:::
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The CrateDB Model Context Protocol (MCP) Server connects AI assistants directly
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to your CrateDB clusters and the CrateDB knowledge base, enabling seamless
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interaction through natural language.
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It serves as a bridge between AI tools and your analytics database,
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allowing you to analyze data, the cluster state, troubleshoot issues, and
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perform operations using conversational prompts.
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:::{rubric} What's inside
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:::
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::::{grid} 1 2 2 2
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:gutter: 2
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:::{grid-item-card} {material-outlined}`integration_instructions;2em` Python package
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:link: https://pypi.org/project/cratedb-mcp/
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:link-type: url
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:link-alt: CrateDB MCP Server Python package `cratedb-mcp`
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For installing and using the package, please consult the README
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document.
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:::
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:::{grid-item-card} {material-outlined}`description;2em` Usage
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:link: https://github.com/crate/cratedb-mcp/blob/main/README.md
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:link-type: url
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:link-alt: CrateDB MCP Server README
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README document about how to install and configure the CrateDB MCP Server.
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:::
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:::{grid-item-card} {material-outlined}`not_started;2em` Examples
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:link: https://github.com/crate/cratedb-mcp/tree/main/examples
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:link-type: url
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:link-alt: CrateDB MCP Server examples
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Examples using the CrateDB MCP Server.
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:::
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::::
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:::{caution}
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**Experimental:** Please note that the CrateDB MCP Server is an experimental
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feature provided as-is without warranty or support guarantees. Enterprise
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customers should use this feature at their own discretion.
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:::
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[MCP]: https://modelcontextprotocol.io/

docs/integrate/mcp/index.md

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# Model Context Protocol (MCP)
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```{toctree}
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:maxdepth: 0
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:hidden:
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cratedb-mcp
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Community servers <community>
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```
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## About
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:::{rubric} Introduction
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:::
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[MCP], the Model Context Protocol, is an open protocol that enables seamless
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integration between LLM applications and external data sources and tools.
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Others define MCP as "It's effectively just OpenAPI for LLMs" or "It's the
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USB-C port for AI", providing a uniform way to connect LLMs to resources they
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can use.
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:::{rubric} Details
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:::
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The main entities of MCP are [prompts], [resources], and [tools].
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MCP clients call MCP servers, either by invoking them as a subprocess and
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communicating via Standard Input/Output (stdio), Server-Sent Events (sse),
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or HTTP Streams (streamable-http), see [transports].
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:::{rubric} Discuss
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:::
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To get in touch with us to discuss CrateDB and MCP, head over to GitHub at
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[Model Context Protocol (MCP) @ CrateDB] or the [Community Forum].
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## Usage
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You can use MCP with [CrateDB] and [CrateDB Cloud], either by selecting the
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**CrateDB MCP Server** suitable for Text-to-SQL and documentation retrieval,
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or by using community MCP servers that are compatible with PostgreSQL databases.
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::::{grid} 1 2 2 2
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:margin: 4 4 0 0
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:::{grid-item-card} {material-outlined}`apps;2em` CrateDB MCP Server
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:link: cratedb-mcp
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:link-type: doc
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:link-alt: CrateDB MCP Server
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The CrateDB MCP Server, available on PyPI and popular community hubs.
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:::
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:::{grid-item-card} {material-outlined}`group;2em` Community MCP Servers
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:link: community
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:link-type: doc
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:link-alt: Community MCP Servers
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MCP servers mostly compatible with both PostgreSQL and CrateDB.
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:::
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::::
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To use an MCP server, you need a [client that supports][MCP clients] the
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protocol. The most notable ones are ChatGPT, Claude, Cline, Cursor,
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GitHub Copilot, Mistral AI, OpenAI Agents SDK, VS Code, Windsurf,
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and others.
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[Community Forum]: https://community.cratedb.com/
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[CrateDB]: https://cratedb.com/database
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[CrateDB Cloud]: https://cratedb.com/docs/cloud/
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[MCP]: https://modelcontextprotocol.io/
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[MCP clients]: https://modelcontextprotocol.io/clients
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[Model Context Protocol (MCP) @ CrateDB]: https://github.com/crate/crate-clients-tools/discussions/234
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[Prompts]: https://modelcontextprotocol.io/docs/concepts/prompts
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[Resources]: https://modelcontextprotocol.io/docs/concepts/resources
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[Tools]: https://modelcontextprotocol.io/docs/concepts/tools
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[Transports]: https://modelcontextprotocol.io/docs/concepts/transports

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