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fixed merge conflicts in genai course
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  • asciidoc/courses/genai-mcp-build-custom-tools-python/modules

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asciidoc/courses/genai-mcp-build-custom-tools-python/modules/1-getting-started/lessons/1-mcp-python-sdk/lesson.adoc

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@@ -249,15 +249,9 @@ The Streamable HTTP transport method exposes the tools through a HTTP server, wi
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[source,python]
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----
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mcp.run(
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<<<<<<< HEAD
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transport="streamable-http",
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host="127.0.0.1",
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port=8000,
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=======
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transport="http",
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host="127.0.0.1",
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port=8000,
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>>>>>>> 2b278d50 (use different attribute for greeting example)
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path="/mcp"
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)
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asciidoc/courses/genai-mcp-build-custom-tools-python/modules/1-getting-started/lessons/3c-create-first-server/lesson.adoc

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@@ -244,4 +244,4 @@ In this challenge, you successfully built your first MCP server from scratch:
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* **Interactive testing** - Tested the server with the Python client for immediate feedback
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In the next module, you will learn about context management for handling server lifecycle and resource management, and you'll start building tools that connect to Neo4j.
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In the next module, you will learn about context management for handling server lifecycle and resource management, and you'll start building tools that connect to Neo4j.

asciidoc/courses/genai-mcp-build-custom-tools-python/modules/2-database-features/lessons/2c-add-neo4j-connection/lesson.adoc

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@@ -68,6 +68,7 @@ NEO4J_DATABASE={instance-database}
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[NOTE]
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.The .env file is already in .gitignore
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The `.env` file is already in `.gitignore` so your credentials won't be committed to version control.
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asciidoc/courses/genai-mcp-build-custom-tools-python/modules/3-integration-advanced/lessons/3-advanced-features/lesson.adoc

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@@ -47,6 +47,7 @@ Use sampling when you need:
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* Recommendations or insights derived from data
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[NOTE]
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.Sampling requires client support
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====
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Sampling requires client support and adds processing overhead. The client must support the sampling capability for this feature to work.
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* Form-based interfaces benefit from autocomplete
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[NOTE]
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.Completions requires using the low-level Server API
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Completions require using the low-level `Server` API instead of FastMCP's decorator-based approach.
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