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