| 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