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vector-search-workflows

vector-search-workflows

Vector search indexing and querying workflows using MCP Vector Search, including setup, reindexing, auto-index strategies, and MCP integration.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

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",
      "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/model-context
  • universal/main/model-context-builder
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