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Add SchemaCrawler AI (#90)
* Add SchemaCrawler AI MCP Server * Use avatar for image * Update description
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servers/schemacrawler-ai/server.yaml

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name: schemacrawler-ai
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image: schemacrawler/schemacrawler-ai
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type: server
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longLived: true
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meta:
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category: database
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tags:
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- ai
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- database
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about:
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title: SchemaCrawler AI
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description: >-
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The SchemaCrawler AI MCP Server enables natural language interaction with
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your database schema using an MCP client in "Agent" mode. It allows users
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to explore tables, columns, foreign keys, triggers, stored procedures and
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more simply by asking questions like "Explain the code for the interest
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calculation stored procedure". You can also ask it to help with SQL,
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since it knows your schema. This is ideal for developers, DBAs, and data
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analysts who want to streamline schema comprehension and query
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development without diving into dense documentation.
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icon: https://avatars.githubusercontent.com/u/58572?v=4
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source:
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project: 'https://github.com/schemacrawler/SchemaCrawler-AI'
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run:
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volumes:
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- '{{schemacrawler-ai.volume.host_share}}:/share'
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config:
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description: Configure SchemaCrawler AI and its connection to the database
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secrets:
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- name: schemacrawler-ai.database_user
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env: SCHCRWLR_DATABASE_USER
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example: SA
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description: '--user Database user name'
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- name: schemacrawler-ai.database_password
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env: SCHCRWLR_DATABASE_PASSWORD
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example: super_S3cret
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description: '--password Database user password'
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env:
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- name: SCHCRWLR_JDBC_URL
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example: 12.12.12.12
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value: '{{schemacrawler-ai.url_connection.jdbc_url}}'
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- name: SCHCRWLR_SERVER
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example: 12.12.12.12
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value: '{{schemacrawler-ai.server_connection.server}}'
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- name: SCHCRWLR_HOST
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example: 12.12.12.12
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value: '{{schemacrawler-ai.server_connection.host}}'
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- name: SCHCRWLR_PORT
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example: 9999
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value: '{{schemacrawler-ai.server_connection.port}}'
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- name: SCHCRWLR_DATABASE
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example: public
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value: '{{schemacrawler-ai.server_connection.database}}'
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- name: SCHCRWLR_INFO_LEVEL
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example: standard
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value: '{{schemacrawler-ai.general.info_level}}'
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- name: SCHCRWLR_LOG_LEVEL
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example: ALL
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value: '{{schemacrawler-ai.general.log_level}}'
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parameters:
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type: object
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properties:
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url_connection:
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type: object
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properties:
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jdbc_url:
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type: string
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description: '--url JDBC URL for database connection'
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required:
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- jdbc_url
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server_connection:
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type: object
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properties:
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server:
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type: string
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description: '--server SchemaCrawler database plugin'
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host:
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type: string
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description: '--host Database host (optional)'
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port:
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type: integer
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description: '--port Database port (optional)'
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database:
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type: string
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description: '--database Database to connect to (optional)'
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required:
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- server
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general:
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type: object
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properties:
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info_level:
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type: string
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description: '--info-level How much database metadata to retrieve'
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default: standard
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required:
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- info_level
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volume:
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type: object
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properties:
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host_share:
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type: string
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description: Host volume to map within the Docker container
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required:
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- host_share
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anyOf:
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- required:
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- url_connection
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- required:
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- server_connection

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