AI-native Contextual Code Engine. Rust core with Python bindings, exposing a CLI, Python SDK, and MCP server for Claude Code / Codex CLI.
OpenACE combines multi-signal retrieval (BM25 full-text + vector kNN + exact match + graph expansion + AST chunk search) with Reciprocal Rank Fusion to deliver high-quality code search across Python, TypeScript, JavaScript, Rust, Go, and Java.
pip install "openace[mcp,openai]" # Index a project openace index /path/to/project --embedding siliconflow # Search openace search "user authentication" -p /path/to/project --embedding siliconflow # Start MCP server openace serve /path/to/project --embedding siliconflow
Add to your project's .mcp.json:
{
"mcpServers": {
"openace": {
"command": "openace",
"args": ["serve", ".", "--embedding", "siliconflow"],
"env": {
"OPENACE_EMBEDDING_API_KEY": "your-api-key"
}
}
}
}Or use uvx for zero-install (once published to PyPI):
{
"mcpServers": {
"openace": {
"command": "uvx",
"args": ["openace", "serve", ".", "--embedding", "siliconflow"],
"env": {
"OPENACE_EMBEDDING_API_KEY": "your-api-key"
}
}
}
}codex mcp add openace -- uvx openace serve . --embedding siliconflowOpenACE supports any OpenAI-compatible embedding/reranking API. Configure via CLI flags or environment variables:
{
"mcpServers": {
"openace": {
"command": "openace",
"args": [
"serve", ".",
"--embedding", "openai",
"--reranker", "siliconflow"
],
"env": {
"OPENACE_EMBEDDING_API_KEY": "your-embedding-key",
"OPENACE_EMBEDDING_BASE_URL": "https://api.your-provider.com/v1",
"OPENACE_RERANKER_API_KEY": "your-reranker-key",
"OPENACE_RERANKER_BASE_URL": "https://api.your-reranker.com/v1"
}
}
}
}| Variable | Description |
|---|---|
OPENACE_EMBEDDING_API_KEY |
API key for embedding provider |
OPENACE_EMBEDDING_BASE_URL |
Custom base URL for embedding API |
OPENACE_EMBEDDING_DIM |
Override embedding vector dimension |
OPENACE_RERANKER_API_KEY |
API key for reranker provider |
OPENACE_RERANKER_BASE_URL |
Custom base URL for reranker API |
OPENACE_EMBEDDING |
Default embedding provider for serve |
OPENACE_RERANKER |
Default reranker for serve |
| Name | Model | Requires |
|---|---|---|
siliconflow |
Qwen/Qwen3-Embedding-8B (1024-dim) | openace[openai] + API key |
openai |
text-embedding-3-small | openace[openai] + API key |
local |
all-MiniLM-L6-v2 (384-dim) | openace[onnx] |
none |
BM25 only, no vector search | (default) |
| Name | Backend | Requires |
|---|---|---|
auto |
Matches embedding provider | (default) |
siliconflow |
Qwen/Qwen3-Reranker-8B | openace[openai] + API key |
cohere |
Cohere Rerank | openace[rerank-cohere] + API key |
cross_encoder |
Local cross-encoder model | openace[rerank-local] |
rule_based |
Heuristic (no API needed) | (built-in) |
Search for code by natural language query. Returns file-level results with code snippets, match signals, and file outlines.
Look up symbols by exact name. Returns definitions with file path, line range, and signature.
Get all symbols defined in a file. Returns a structural overview with symbol kinds, names, and line ranges.
from openace import Engine engine = Engine("/path/to/project") engine.index() # Semantic search results = engine.search("parse XML", limit=10) for r in results: print(f"{r.file_path}:{r.line_range[0]} {r.name} ({r.kind})") # Exact lookup symbols = engine.find_symbol("MyClass") # File outline outline = engine.get_file_outline("src/main.py")
# Default install (includes MCP server, OpenAI/SiliconFlow embedding & reranking) pip install openace # With local ONNX embedding (no API key needed) pip install "openace[onnx]" # With Cohere reranker pip install "openace[rerank-cohere]" # Development pip install -e ".[dev]"
Source files --> Scanner --> Parser (tree-sitter) --> Indexer --> Storage
|
SQLite (graph/relations)
Tantivy (BM25 full-text)
usearch (vector kNN)
|
Query --> CLI/SDK/MCP --> Retrieval (BM25 + vector + exact + graph + chunk)
|
RRF Fusion --> Reranker --> Results
- Rust core handles all performance-critical operations (parsing, indexing, storage, retrieval)
- Python layer provides the SDK, CLI, MCP server, and pluggable embedding/reranking providers
- tree-sitter for multi-language AST parsing
- Triple-backend storage: SQLite for graph/relations, Tantivy for BM25, usearch for HNSW vector search
- CJK bigram tokenization in BM25 for Chinese/Japanese/Korean query support
Python, TypeScript, JavaScript, Rust, Go, Java.
Requires Rust >= 1.85.0 and Python >= 3.10.
git clone https://github.com/Kosthi/OpenACE.git cd OpenACE pip install maturin maturin develop --release pip install -e ".[dev]"
MIT