Semcode
About
An MCP (Model Context Protocol) server providing hybrid semantic search over code across a set of GitHub repositories that you list in config.yaml. It parses symbols with Tree-sitter and indexes both code and git commit history, so AI clients can query them by natural language or
Details
- Author
- GoodbyePlanet
- Downloads
- 421
- Categories
- Search, Developer Tools, Knowledge Base, Other
Jump to
- Hybrid retrieval combining dense embeddings and BM25
- Incremental indexing—only changed files are re-embedded
- Supports 19 programming languages with framework-aware parsing
- Optional git commit history indexing with full diffs
- MCP tools for search, symbol lookup, and reindexing
- HTTP API for triggering index from CI/CD pipelines
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
SemcodeCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install Python 3.12+, Docker, and a GitHub token. Clone the repo, run uv sync, copy .env.example to .env and set GITHUB_TOKEN, then copy config.example.yaml to config.yaml and list the repositories to index. Start the server with make docker-up-jina (local embeddings) or make docker-up (hosted provider). Connect AI clients by pointing them at http://localhost:8090/mcp.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"semcode": {
"semcode": {
"transport": "http",
"url": "http://localhost:8090/mcp"
}
}
}
}McpServers
{
"semcode": {
"transport": "http",
"url": "http://localhost:8090/mcp"
}
}semcode
An MCP (Model Context Protocol) server providing hybrid semantic search over code across a set of
GitHub repositories that you list in config.yaml. It parses symbols
with Tree-sitter and indexes both code and git commit history, so AI clients can query them by
natural language or by symbol name.
Hybrid retrieval combines dense embeddings with BM25, so both natural-language queries
("where do we publish order events?") and symbol-name lookups (PlaceOrderRequest) work well.
Submitted on mcpservers.org
How it works
1. Fetches source files from configured GitHub repositories
2. Parses code symbols (functions, classes, methods, components) using Tree-sitter
3. Generates two embeddings per symbol — a dense semantic vector (pluggable provider: Jina Code V2 by default, or
Voyage / OpenAI / Ollama) and a BM25 sparse vector keyed on code-identifier tokens (camelCase / snake_case split into
subwords)
4. Stores both in Qdrant and retrieves them with hybrid search — Reciprocal Rank Fusion (RRF) over the dense and
sparse results — so natural-language queries and symbol-name lookups both work well
5. Optionally indexes commit history into a separate Qdrant collection (dense-only)
6. Exposes search and indexing tools through the MCP protocol (and a small HTTP API)
Indexing is incremental — files are skipped when their Git blob SHA matches the last indexed version.
Files that no longer exist (or parse to zero symbols) are cleaned up automatically. Pass force: true
to re-embed everything.
Supported languages
Language is detected automatically from file extension or filename — no configuration needed.
Go, Java, Python, TypeScript / JavaScript (React), Rust, C#, C, C++, Ruby, PHP, Kotlin, Scala, Swift, Dart, Bash, SQL,
Lua, R, Dockerfile, Docker Compose, Markdown, JSON, HTML, CSS, XML.
Most parsers are framework-aware where it matters — Spring stereotypes and HTTP routes for Java/Kotlin, FastAPI/Pydantic
for Python, ASP.NET for C#, Rails for Ruby, Laravel/Symfony for PHP, React/SwiftUI/Flutter widgets, etc. See
server/parser/ for the per-language extraction details.
Setup
Prerequisites: Python 3.12+, Docker, GitHub token
```bash
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