Vector Search Workflows (MCP Vector Search) Overview
Use mcp-vector-search to index codebases into ChromaDB and search via semantic embeddings. The recommended flow is setup (init + index + MCP integration), then search, and use index or auto-index to keep data fresh.
Quick Start pip install mcp-vector-search mcp-vector-search setup mcp-vector-search search "authentication logic"
setup detects languages, initializes config, indexes the repo, and configures MCP integrations (Claude Code, Cursor, etc.).
Core Commands Indexing mcp-vector-search index mcp-vector-search index --force mcp-vector-search index reindex --all --force mcp-vector-search index reindex path/to/file.py
Auto-Index Strategies mcp-vector-search auto-index setup --method all mcp-vector-search auto-index status mcp-vector-search auto-index check --auto-reindex --max-files 10 mcp-vector-search auto-index teardown --method all
Search mcp-vector-search search "error handling patterns" mcp-vector-search search "vector store initialization"
Status + Doctor mcp-vector-search status mcp-vector-search doctor
MCP Integration Pattern
setup uses native claude mcp add when available, otherwise falls back to .mcp.json.
Typical .mcp.json entry:
{ "mcpServers": { "mcp-vector-search": { "type": "stdio", "command": "uv", "args": ["run", "mcp-vector-search", "mcp"], "env": { "MCP_ENABLE_FILE_WATCHING": "true" } } } }
Reindex Triggers Dependency updates or parser changes Large refactors Adding new languages or file extensions Tool upgrades (version tracking triggers reindex) Local Patterns Use uv for dev installs: uv sync --dev Use setup --force to rebuild config + index after tool upgrades Keep file watching on via MCP_ENABLE_FILE_WATCHING=true Related Skills toolchains/ai/protocols/mcp universal/main/mcp-builder