vector-search-workflows

name	vector-search-workflows
description	Vector search indexing and querying workflows using MCP Vector Search, including setup, reindexing, auto-index strategies, and MCP integration.
user-invocable	false
disable-model-invocation	true
version	1.0.0
category	toolchain
author	Claude MPM Team
license	MIT
progressive_disclosure	{"entry_point":{"summary":"Index a codebase with mcp-vector-search, keep it fresh with auto-indexing, and query via CLI or MCP integration.","when_to_use":"Building semantic search for codebases, setting up MCP search tools, or troubleshooting indexing and reindexing workflows.","quick_start":"1. mcp-vector-search setup 2. mcp-vector-search search \"query\" 3. mcp-vector-search index --force when schema changes"}}
tags	["vector-search","embeddings","indexing","search","mcp"]

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",