bump: version 0.46.1 → 0.46.2

fix(smithery): Enable JSON response format for scanner compatibility

CHANGELOG.md

@@ -1,3 +1,9 @@
+## v0.46.2 (2025-11-22)
+
+### Fix
+
+- **smithery**: Enable JSON response format for scanner compatibility
+
 ## v0.46.1 (2025-11-22)
 
 ### Perf

README.md

@@ -1,12 +1,11 @@
-```markdown
 <p align="center">
   <img src="astrolabe.svg" alt="Nextcloud MCP Server" width="128" height="128">
 </p>
 
 # Nextcloud MCP Server
 
-[![smithery badge](https://smithery.ai/badge/@cbcoutinho/nextcloud-mcp-server)](https://smithery.ai/server/@cbcoutinho/nextcloud-mcp-server)
 [![Docker Image](https://img.shields.io/badge/docker-ghcr.io/cbcoutinho/nextcloud--mcp--server-blue)](https://github.com/cbcoutinho/nextcloud-mcp-server/pkgs/container/nextcloud-mcp-server)
+[![smithery badge](https://smithery.ai/badge/@cbcoutinho/nextcloud-mcp-server)](https://smithery.ai/server/@cbcoutinho/nextcloud-mcp-server)
 
 **A production-ready MCP server that connects AI assistants to your Nextcloud instance.**
 
@@ -224,4 +223,3 @@ This project is licensed under the AGPL-3.0 License. See [LICENSE](./LICENSE) fo
 - [Model Context Protocol](https://github.com/modelcontextprotocol)
 - [MCP Python SDK](https://github.com/modelcontextprotocol/python-sdk)
 - [Nextcloud](https://nextcloud.com/)
-```

charts/nextcloud-mcp-server/Chart.yaml

@@ -2,8 +2,8 @@ apiVersion: v2
 name: nextcloud-mcp-server
 description: A Helm chart for Nextcloud MCP Server - enables AI assistants to interact with Nextcloud
 type: application
-version: 0.46.1
+version: 0.46.2
-appVersion: "0.46.1"
+appVersion: "0.46.2"
 keywords:
   - nextcloud
   - mcp

nextcloud_mcp_server/app.py

@@ -1072,7 +1072,11 @@ def get_app(transport: str = "sse", enabled_apps: list[str] | None = None):
         # ADR-016: Use Smithery lifespan for stateless mode, BasicAuth otherwise
         if deployment_mode == DeploymentMode.SMITHERY_STATELESS:
             logger.info("Configuring MCP server for Smithery stateless mode")
-            mcp = FastMCP("Nextcloud MCP", lifespan=app_lifespan_smithery)
+            # json_response=True returns plain JSON-RPC instead of SSE format,
+            # required for Smithery scanner compatibility
+            mcp = FastMCP(
+                "Nextcloud MCP", lifespan=app_lifespan_smithery, json_response=True
+            )
         else:
             logger.info("Configuring MCP server for BasicAuth mode")
             mcp = FastMCP("Nextcloud MCP", lifespan=app_lifespan_basic)

nextcloud_mcp_server/server/semantic.py

@@ -335,27 +335,6 @@ def configure_semantic_tools(mcp: FastMCP):
         Note: Requires MCP client to support sampling. If sampling is unavailable,
         the tool gracefully degrades to returning documents with an explanation.
         The client may prompt the user to approve the sampling request.
-
-        Examples:
-            >>> # Query about objectives across multiple apps
-            >>> result = await nc_semantic_search_answer(
-            ...     query="What are my Q1 2025 project goals?",
-            ...     ctx=ctx
-            ... )
-            >>> print(result.generated_answer)
-            "Based on Document 1 (note: Project Kickoff), Document 2 (calendar event:
-            Q1 Planning Meeting), and Document 3 (deck card: Implement semantic search),
-            your main goals are: 1) Improve semantic search accuracy by 20%,
-            2) Deploy new embedding model, 3) Reduce indexing latency..."
-
-            >>> # Query about appointments
-            >>> result = await nc_semantic_search_answer(
-            ...     query="When is my next dentist appointment?",
-            ...     ctx=ctx,
-            ...     limit=10
-            ... )
-            >>> len(result.sources)  # Calendar events and related notes
-            3
         """
         # 1. Retrieve relevant documents via existing semantic search
         search_response = await nc_semantic_search(

nextcloud_mcp_server/server/webdav.py

@@ -64,20 +64,6 @@ def configure_webdav_tools(mcp: FastMCP):
             - Text files are decoded to UTF-8
             - Documents (PDF, DOCX, etc.) are parsed and text is extracted
             - Other binary files are base64 encoded
-
-        Examples:
-            # Read a text file
-            result = await nc_webdav_read_file("Documents/readme.txt")
-            logger.info(result['content'])  # Decoded text content
-
-            # Read a PDF document (automatically parsed)
-            result = await nc_webdav_read_file("Documents/report.pdf")
-            logger.info(result['content'])  # Extracted text from PDF
-            logger.info(result['parsing_metadata'])  # Document parsing info
-
-            # Read a binary file
-            result = await nc_webdav_read_file("Images/photo.jpg")
-            logger.info(result['encoding'])  # 'base64'
         """
         client = await get_client(ctx)
         content, content_type = await client.webdav.read_file(path)

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "nextcloud-mcp-server"
-version = "0.46.1"
+version = "0.46.2"
 description = "Model Context Protocol (MCP) server for Nextcloud integration - enables AI assistants to interact with Nextcloud data"
 authors = [
     {name = "Chris Coutinho", email = "chris@coutinho.io"}

uv.lock

@@ -1936,7 +1936,7 @@ wheels = [
 
 [[package]]
 name = "nextcloud-mcp-server"
-version = "0.46.1"
+version = "0.46.2"
 source = { editable = "." }
 dependencies = [
     { name = "aiosqlite" },