feat: rename search tool to search_notes

CLAUDE.md

@@ -107,15 +107,15 @@ See the [README.md](README.md) file for a project overview.
       1d", "1 week")
 
   **Search & Discovery:**
-    - `search(query, page, page_size)` - Full-text search across all content with filtering options
+    - `search_notes(query, page, page_size)` - Full-text search across all content with filtering options
 
   **Visualization:**
     - `canvas(nodes, edges, title, folder)` - Generate Obsidian canvas files for knowledge graph visualization
 
 - MCP Prompts for better AI interaction:
     - `ai_assistant_guide()` - Guidance on effectively using Basic Memory tools for AI assistants
     - `continue_conversation(topic, timeframe)` - Continue previous conversations with relevant historical context
-    - `search(query, after_date)` - Search with detailed, formatted results for better context understanding
+    - `search_notes(query, after_date)` - Search with detailed, formatted results for better context understanding
     - `recent_activity(timeframe)` - View recently changed items with formatted output
     - `json_canvas_spec()` - Full JSON Canvas specification for Obsidian visualization
 

README.md

@@ -285,7 +285,8 @@ for OS X):
 }
 ```
 
-If you want to use a specific project (see [Multiple Projects](docs/User%20Guide.md#multiple-projects)), update your Claude Desktop
+If you want to use a specific project (see [Multiple Projects](docs/User%20Guide.md#multiple-projects)), update your
+Claude Desktop
 config:
 
 ```json
@@ -320,7 +321,7 @@ basic-memory sync --watch
 write_note(title, content, folder, tags) - Create or update notes
 read_note(identifier, page, page_size) - Read notes by title or permalink
 build_context(url, depth, timeframe) - Navigate knowledge graph via memory:// URLs
-search(query, page, page_size) - Search across your knowledge base
+search_notes(query, page, page_size) - Search across your knowledge base
 recent_activity(type, depth, timeframe) - Find recently updated information
 canvas(nodes, edges, title, folder) - Generate knowledge visualizations
 ```

docs/AI Assistant Guide.md

@@ -53,7 +53,7 @@ content = await read_note("specs/search-design")       # By path
 content = await read_note("memory://specs/search")     # By memory URL
 
 # Searching for knowledge
-results = await search(
+results = await search_notes(
     query="authentication system",      # Text to search for
     page=1,                             # Optional: Pagination
     page_size=10                        # Optional: Results per page
@@ -154,7 +154,7 @@ Users will interact with Basic Memory in patterns like:
    Human: "What were our decisions about auth?"
 
    You: Let me find that information for you.
-   [Use search() to find relevant notes]
+   [Use search_notes() to find relevant notes]
    [Then build_context() to understand connections]
    ```
 
@@ -251,7 +251,7 @@ When creating relations, you can:
 # Example workflow for creating notes with effective relations
 async def create_note_with_effective_relations():
     # Search for existing entities to reference
-    search_results = await search("travel")
+    search_results = await search_notes("travel")
     existing_entities = [result.title for result in search_results.primary_results]
 
     # Check if specific entities exist
@@ -323,7 +323,7 @@ Common issues to watch for:
        content = await read_note("Document")
    except:
        # Try search instead
-       results = await search("Document")
+       results = await search_notes("Document")
        if results and results.primary_results:
            # Found something similar
            content = await read_note(results.primary_results[0].permalink)
@@ -369,7 +369,7 @@ Common issues to watch for:
    - **Create deliberate relations**: Connect each note to at least 2-3 related entities
    - **Use existing entities**: Before creating a new relation, search for existing entities
    - **Verify wikilinks**: When referencing `[[Entity]]`, use exact titles of existing notes
-   - **Check accuracy**: Use `search()` or `recent_activity()` to confirm entity titles
+   - **Check accuracy**: Use `search_notes()` or `recent_activity()` to confirm entity titles
    - **Use precise relation types**: Choose specific relation types that convey meaning (e.g., "implements" instead of "relates_to")
    - **Consider bidirectional relations**: When appropriate, create inverse relations in both entities
 

docs/Technical Information.md

@@ -196,7 +196,7 @@ flowchart TD
     end
 
     BMCP <-->|"write_note() read_note()"| KnowledgeFiles
-    BMCP <-->|"search() build_context()"| KnowledgeIndex
+    BMCP <-->|"search_notes() build_context()"| KnowledgeIndex
     KnowledgeFiles <-.->|Sync Process| KnowledgeIndex
     KnowledgeFiles <-->|Direct Editing| Editors((Text Editors & Git))
 

src/basic_memory/cli/commands/tool.py

@@ -12,7 +12,7 @@
 from basic_memory.mcp.tools import build_context as mcp_build_context
 from basic_memory.mcp.tools import read_note as mcp_read_note
 from basic_memory.mcp.tools import recent_activity as mcp_recent_activity
-from basic_memory.mcp.tools import search as mcp_search
+from basic_memory.mcp.tools import search_notes as mcp_search
 from basic_memory.mcp.tools import write_note as mcp_write_note
 
 # Import prompts
@@ -180,8 +180,8 @@ def recent_activity(
         raise
 
 
-@tool_app.command()
-def search(
+@tool_app.command("search-notes")
+def search_notes(
     query: str,
     permalink: Annotated[bool, typer.Option("--permalink", help="Search permalink values")] = False,
     title: Annotated[bool, typer.Option("--title", help="Search title values")] = False,

src/basic_memory/mcp/prompts/continue_conversation.py

@@ -14,7 +14,7 @@
 from basic_memory.mcp.server import mcp
 from basic_memory.mcp.tools.build_context import build_context
 from basic_memory.mcp.tools.recent_activity import recent_activity
-from basic_memory.mcp.tools.search import search
+from basic_memory.mcp.tools.search import search_notes
 from basic_memory.schemas.base import TimeFrame
 from basic_memory.schemas.memory import GraphContext
 from basic_memory.schemas.search import SearchQuery, SearchItemType
@@ -47,7 +47,7 @@ async def continue_conversation(
 
     # If topic provided, search for it
     if topic:
-        search_results = await search(
+        search_results = await search_notes(
             SearchQuery(text=topic, after_date=timeframe, types=[SearchItemType.ENTITY])
         )
 
@@ -93,7 +93,7 @@ async def continue_conversation(
         ## Next Steps
 
         You can:
-        - Explore more with: `search({{"text": "{topic}"}})`
+        - Explore more with: `search_notes({{"text": "{topic}"}})`
         - See what's changed: `recent_activity(timeframe="{timeframe or "7d"}")`
         - **Record new learnings or decisions from this conversation:** `write_note(title="[Create a meaningful title]", content="[Content with observations and relations]")`
 

src/basic_memory/mcp/prompts/search.py

@@ -10,7 +10,7 @@
 from pydantic import Field
 
 from basic_memory.mcp.server import mcp
-from basic_memory.mcp.tools.search import search as search_tool
+from basic_memory.mcp.tools.search import search_notes as search_tool
 from basic_memory.schemas.base import TimeFrame
 from basic_memory.schemas.search import SearchQuery, SearchResponse
 
@@ -144,9 +144,9 @@ def format_search_results(
         ## Next Steps
 
         You can:
-        - Refine your search: `search("{query} AND additional_term")`
-        - Exclude terms: `search("{query} NOT exclude_term")`
-        - View more results: `search("{query}", after_date=None)`
+        - Refine your search: `search_notes("{query} AND additional_term")`
+        - Exclude terms: `search_notes("{query} NOT exclude_term")`
+        - View more results: `search_notes("{query}", after_date=None)`
         - Check recent activity: `recent_activity()`
 
         ## Synthesize and Capture Knowledge

src/basic_memory/mcp/resources/ai_assistant_guide.md

@@ -49,7 +49,7 @@ content = await read_note("specs/search-design")  # By path
 content = await read_note("memory://specs/search")  # By memory URL
 
 # Searching for knowledge
-results = await search(
+results = await search_notes(
     query="authentication system",  # Text to search for
     page=1,  # Optional: Pagination
     page_size=10  # Optional: Results per page
@@ -154,7 +154,7 @@ Users will interact with Basic Memory in patterns like:
    Human: "What were our decisions about auth?"
 
    You: Let me find that information for you.
-   [Use search() to find relevant notes]
+   [Use search_notes() to find relevant notes]
    [Then build_context() to understand connections]
    ```
 
@@ -263,7 +263,7 @@ When creating relations, you can:
 # Example workflow for creating notes with effective relations
 async def create_note_with_effective_relations():
     # Search for existing entities to reference
-    search_results = await search("travel")
+    search_results = await search_notes("travel")
     existing_entities = [result.title for result in search_results.primary_results]
 
     # Check if specific entities exist
@@ -335,7 +335,7 @@ Common issues to watch for:
        content = await read_note("Document")
    except:
        # Try search instead
-       results = await search("Document")
+       results = await search_notes("Document")
        if results and results.primary_results:
            # Found something similar
            content = await read_note(results.primary_results[0].permalink)
@@ -381,7 +381,7 @@ Common issues to watch for:
     - **Create deliberate relations**: Connect each note to at least 2-3 related entities
     - **Use existing entities**: Before creating a new relation, search for existing entities
     - **Verify wikilinks**: When referencing `[[Entity]]`, use exact titles of existing notes
-    - **Check accuracy**: Use `search()` or `recent_activity()` to confirm entity titles
+    - **Check accuracy**: Use `search_notes()` or `recent_activity()` to confirm entity titles
     - **Use precise relation types**: Choose specific relation types that convey meaning (e.g., "implements" instead
       of "relates_to")
     - **Consider bidirectional relations**: When appropriate, create inverse relations in both entities

src/basic_memory/mcp/tools/__init__.py

@@ -12,7 +12,7 @@
 from basic_memory.mcp.tools.recent_activity import recent_activity
 from basic_memory.mcp.tools.read_note import read_note
 from basic_memory.mcp.tools.write_note import write_note
-from basic_memory.mcp.tools.search import search
+from basic_memory.mcp.tools.search import search_notes
 from basic_memory.mcp.tools.canvas import canvas
 
 __all__ = [
@@ -22,6 +22,6 @@
     "read_content",
     "read_note",
     "recent_activity",
-    "search",
+    "search_notes",
     "write_note",
 ]

src/basic_memory/mcp/tools/read_note.py

@@ -6,7 +6,7 @@
 
 from basic_memory.mcp.async_client import client
 from basic_memory.mcp.server import mcp
-from basic_memory.mcp.tools.search import search
+from basic_memory.mcp.tools.search import search_notes
 from basic_memory.mcp.tools.utils import call_get
 from basic_memory.schemas.memory import memory_url_path
 from basic_memory.schemas.search import SearchQuery
@@ -63,7 +63,7 @@ async def read_note(identifier: str, page: int = 1, page_size: int = 10) -> str:
 
     # Fallback 1: Try title search via API
     logger.info(f"Search title for: {identifier}")
-    title_results = await search(SearchQuery(title=identifier))
+    title_results = await search_notes(SearchQuery(title=identifier))
 
     if title_results and title_results.results:
         result = title_results.results[0]  # Get the first/best match
@@ -87,7 +87,7 @@ async def read_note(identifier: str, page: int = 1, page_size: int = 10) -> str:
 
     # Fallback 2: Text search as a last resort
     logger.info(f"Title search failed, trying text search for: {identifier}")
-    text_results = await search(SearchQuery(text=identifier))
+    text_results = await search_notes(SearchQuery(text=identifier))
 
     # We didn't find a direct match, construct a helpful error message
     if not text_results or not text_results.results:

src/basic_memory/mcp/tools/search.py

@@ -11,7 +11,7 @@
 @mcp.tool(
     description="Search across all content in the knowledge base.",
 )
-async def search(query: SearchQuery, page: int = 1, page_size: int = 10) -> SearchResponse:
+async def search_notes(query: SearchQuery, page: int = 1, page_size: int = 10) -> SearchResponse:
     """Search across all content in the knowledge base.
 
     This tool searches the knowledge base using full-text search, pattern matching,
@@ -36,34 +36,34 @@ async def search(query: SearchQuery, page: int = 1, page_size: int = 10) -> Sear
 
     Examples:
         # Basic text search
-        results = await search(SearchQuery(text="project planning"))
+        results = await search_notes(SearchQuery(text="project planning"))
 
         # Boolean AND search (both terms must be present)
-        results = await search(SearchQuery(text="project AND planning"))
+        results = await search_notes(SearchQuery(text="project AND planning"))
 
         # Boolean OR search (either term can be present)
-        results = await search(SearchQuery(text="project OR meeting"))
+        results = await search_notes(SearchQuery(text="project OR meeting"))
 
         # Boolean NOT search (exclude terms)
-        results = await search(SearchQuery(text="project NOT meeting"))
+        results = await search_notes(SearchQuery(text="project NOT meeting"))
 
         # Boolean search with grouping
-        results = await search(SearchQuery(text="(project OR planning) AND notes"))
+        results = await search_notes(SearchQuery(text="(project OR planning) AND notes"))
 
         # Search with type filter
-        results = await search(SearchQuery(
+        results = await search_notes(SearchQuery(
             text="meeting notes",
             types=["entity"],
         ))
 
         # Search for recent content
-        results = await search(SearchQuery(
+        results = await search_notes(SearchQuery(
             text="bug report",
             after_date="1 week"
         ))
 
         # Pattern matching on permalinks
-        results = await search(SearchQuery(
+        results = await search_notes(SearchQuery(
             permalink_match="docs/meeting-*"
         ))
     """

static/ai_assistant_guide.md

@@ -49,7 +49,7 @@ content = await read_note("specs/search-design")  # By path
 content = await read_note("memory://specs/search")  # By memory URL
 
 # Searching for knowledge
-results = await search(
+results = await search_notes(
     query="authentication system",  # Text to search for
     page=1,  # Optional: Pagination
     page_size=10  # Optional: Results per page
@@ -154,7 +154,7 @@ Users will interact with Basic Memory in patterns like:
    Human: "What were our decisions about auth?"
 
    You: Let me find that information for you.
-   [Use search() to find relevant notes]
+   [Use search_notes() to find relevant notes]
    [Then build_context() to understand connections]
    ```
 
@@ -263,7 +263,7 @@ When creating relations, you can:
 # Example workflow for creating notes with effective relations
 async def create_note_with_effective_relations():
     # Search for existing entities to reference
-    search_results = await search("travel")
+    search_results = await search_notes("travel")
     existing_entities = [result.title for result in search_results.primary_results]
 
     # Check if specific entities exist
@@ -335,7 +335,7 @@ Common issues to watch for:
        content = await read_note("Document")
    except:
        # Try search instead
-       results = await search("Document")
+       results = await search_notes("Document")
        if results and results.primary_results:
            # Found something similar
            content = await read_note(results.primary_results[0].permalink)
@@ -381,7 +381,7 @@ Common issues to watch for:
     - **Create deliberate relations**: Connect each note to at least 2-3 related entities
     - **Use existing entities**: Before creating a new relation, search for existing entities
     - **Verify wikilinks**: When referencing `[[Entity]]`, use exact titles of existing notes
-    - **Check accuracy**: Use `search()` or `recent_activity()` to confirm entity titles
+    - **Check accuracy**: Use `search_notes()` or `recent_activity()` to confirm entity titles
     - **Use precise relation types**: Choose specific relation types that convey meaning (e.g., "implements" instead
       of "relates_to")
     - **Consider bidirectional relations**: When appropriate, create inverse relations in both entities

tests/cli/test_cli_tools.py

@@ -211,7 +211,7 @@ def test_search_basic(cli_env, setup_test_note):
     """Test basic search command."""
     result = runner.invoke(
         tool_app,
-        ["search", "test observation"],
+        ["search-notes", "test observation"],
     )
     assert result.exit_code == 0
 
@@ -235,7 +235,7 @@ def test_search_permalink(cli_env, setup_test_note):
 
     result = runner.invoke(
         tool_app,
-        ["search", permalink, "--permalink"],
+        ["search-notes", permalink, "--permalink"],
     )
     assert result.exit_code == 0
 

tests/mcp/test_tool_read_note.py

@@ -26,7 +26,7 @@ async def mock_call_get():
 @pytest_asyncio.fixture
 async def mock_search():
     """Mock for search tool."""
-    with patch("basic_memory.mcp.tools.read_note.search") as mock:
+    with patch("basic_memory.mcp.tools.read_note.search_notes") as mock:
         # Default to empty results
         mock.return_value = SearchResponse(results=[], current_page=1, page_size=1)
         yield mock