feat(knowledge-base): implement Knowledge Base MCP Server (#57)

Implements RAG capabilities with pgvector for semantic search:

- Intelligent chunking strategies (code-aware, markdown-aware, text)
- Semantic search with vector similarity (HNSW index)
- Keyword search with PostgreSQL full-text search
- Hybrid search using Reciprocal Rank Fusion (RRF)
- Redis caching for embeddings
- Collection management (ingest, search, delete, stats)
- FastMCP tools: search_knowledge, ingest_content, delete_content,
  list_collections, get_collection_stats, update_document

Testing:
- 128 comprehensive tests covering all components
- 58% code coverage (database integration tests use mocks)
- Passes ruff linting and mypy type checking

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

mcp-servers/knowledge-base/chunking/__init__.py

@@ -0,0 +1,19 @@
+"""
+Chunking module for Knowledge Base MCP Server.
+
+Provides intelligent content chunking for different file types
+with overlap and context preservation.
+"""
+
+from chunking.base import BaseChunker, ChunkerFactory
+from chunking.code import CodeChunker
+from chunking.markdown import MarkdownChunker
+from chunking.text import TextChunker
+
+__all__ = [
+    "BaseChunker",
+    "ChunkerFactory",
+    "CodeChunker",
+    "MarkdownChunker",
+    "TextChunker",
+]