dcc-mcp-core-semantic 0.19.4

Native Rust semantic embeddings (fastembed-rs) for dcc-mcp-core

dcc-mcp-core-semantic

Native Rust semantic embeddings for dcc-mcp-core, shipped as a separate PyPI wheel so the main dcc-mcp-core install stays free of ONNX Runtime and the ~25-40 MB wheel size that comes with it.

When to install this

Only when you actually need dense semantic recall for skill / capability search. The default pip install dcc-mcp-core install ships with a HashedEmbedder (zero-dep, hashing-trick + character n-grams) which is enough for ≤100-skill DCC adapters and tolerates morphology variants like render / rendering already.

If your skill catalogue grows to many hundreds of skills, or your agents ask in natural language that does not share token structure with your SKILL.md metadata, install this companion wheel to upgrade OnnxEmbedder to true dense semantic recall.

How to install

pip install 'dcc-mcp-core[semantic]'

This pulls in dcc-mcp-core-semantic (this package) via the [semantic] extra, plus fastembed as a Python-side fallback for platforms where the Rust wheel is not yet available.

You can also install this package directly if you want only the Rust backend without the Python fallback:

pip install dcc-mcp-core dcc-mcp-core-semantic

How it gets used

Your adapter code does not change. Once installed, dcc_mcp_core.OnnxEmbedder() automatically prefers the Rust extension:

from dcc_mcp_core import OnnxEmbedder, VectorSkillIndex

# Loads the BAAI/bge-small-en-v1.5 model on first use, cached to
# ~/.cache/fastembed/ (or wherever DCC_MCP_EMBED_MODEL_DIR points).
emb = OnnxEmbedder()
idx = VectorSkillIndex(embedder=emb)

Configuration

Both env vars are honoured by OnnxEmbedder regardless of which backend serves the call:

Variable	Default	Purpose
DCC_MCP_EMBED_MODEL	BAAI/bge-small-en-v1.5	HuggingFace model name. Must be one of dcc_mcp_core_semantic.native.SUPPORTED_MODELS.
DCC_MCP_EMBED_MODEL_DIR	unset (fastembed default)	On-disk cache for the ONNX model bytes. Pre-place this on a shared mount for firewalled studios.

Build from source

The source lives in the main dcc-mcp-core repository, NOT here. Rust crate: crates/dcc-mcp-semantic/. Wheel build:

cd pkg/dcc-mcp-core-semantic
maturin build --release

ONNX Runtime is pulled in at build time via the ort crate's download-binaries strategy. The wheel that maturin produces is self-contained — end users do not need to install ONNX Runtime separately.

License

MIT, matching dcc-mcp-core.