Fix documentation links and update API section naming

- Update README documentation links to point to full docs site instead of local files
- Add note about MCP/SDK tool calls vs direct client function calls
- Rename "API Interfaces" to "API Reference" across all documentation
- Apply ruff code formatting fixes

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <[email protected]>

Author: abrookins

CLAUDE.md

@@ -222,7 +222,7 @@ ENABLE_TOPIC_EXTRACTION=true
 ENABLE_NER=true
 ```
 
-## API Interfaces
+## API Reference
 
 ### REST API (Port 8000)
 - Session management (`/v1/working-memory/`)

README.md

@@ -57,6 +57,8 @@ results = await client.search_long_term_memory(
 )
 ```
 
+> **Note**: While you can call client functions directly as shown above, using **MCP or SDK-provided tool calls** is recommended for AI agents as it provides better integration, automatic context management, and follows AI-native patterns. See **[Memory Patterns](https://redis.github.io/agent-memory-server/memory-patterns/)** for guidance on when to use each approach.
+
 ### 3. MCP Integration
 
 ```bash
@@ -73,13 +75,13 @@ uv run agent-memory mcp --mode sse --port 9000
 
 ### Key Documentation Sections:
 
-- **[Quick Start Guide](docs/quick-start.md)** - Get up and running in minutes
-- **[Python SDK](docs/python-sdk.md)** - Complete SDK reference with examples
-- **[Vector Store Backends](docs/vector-store-backends.md)** - Configure different vector databases
-- **[Authentication](docs/authentication.md)** - OAuth2/JWT setup for production
-- **[Memory Types](docs/memory-types.md)** - Understanding semantic vs episodic memory
-- **[API Reference](docs/api.md)** - REST API endpoints
-- **[MCP Protocol](docs/mcp.md)** - Model Context Protocol integration
+- **[Quick Start Guide](https://redis.github.io/agent-memory-server/quick-start/)** - Get up and running in minutes
+- **[Python SDK](https://redis.github.io/agent-memory-server/python-sdk/)** - Complete SDK reference with examples
+- **[Vector Store Backends](https://redis.github.io/agent-memory-server/vector-store-backends/)** - Configure different vector databases
+- **[Authentication](https://redis.github.io/agent-memory-server/authentication/)** - OAuth2/JWT setup for production
+- **[Memory Types](https://redis.github.io/agent-memory-server/memory-types/)** - Understanding semantic vs episodic memory
+- **[API Reference](https://redis.github.io/agent-memory-server/api/)** - REST API endpoints
+- **[MCP Protocol](https://redis.github.io/agent-memory-server/mcp/)** - Model Context Protocol integration
 
 ## Architecture
 

docs/README.md

@@ -28,7 +28,7 @@ Understand the fundamentals:
 - **[Recency Boost](recency-boost.md)** - Time-aware memory ranking and intelligent scoring
 - **[Vector Store Backends](vector-store-backends.md)** - Alternative storage backends (Pinecone, Chroma, etc.)
 
-## 🔌 API Interfaces
+## 🔌 API Reference
 
 Choose your integration approach:
 

mkdocs.yml

@@ -100,7 +100,7 @@ nav:
     - Advanced Vector Store Config: vector-store-advanced.md
     - Contextual Grounding: contextual-grounding.md
 
-  - API Interfaces:
+  - API Reference:
     - REST API: api.md
     - MCP Server: mcp.md
     - CLI Reference: cli.md