ZAP RAG MCP Server
Provides access to ZAP's RAG search modes (PLAIN, HYBRID, HYBRID_RERANK) for retrieving code context from a local SQLite index built by the ZAP IntelliJ plugin.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ZAP RAG MCP ServerSearch for 'user authentication' using hybrid_rerank mode"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ZAP RAG MCP Server
Standalone Model Context Protocol (MCP) server that exposes only ZAP’s RAG search modes for other agents (Kilo, Cursor, Claude Desktop, Continue, etc.).
Works with the SQLite index built by the ZAP IntelliJ plugin (rag.db).
Tool | Description |
| DB health, chunk/embedding counts, models, modes |
| Semantic search: PLAIN / HYBRID / HYBRID_RERANK |
Read-only. No write tools, no agent loop — retrieval only.
Modes
Mode | Behavior | Needs |
PLAIN | Cosine over code-chunk embeddings | Index + embeddings |
HYBRID | Weighted class summaries + code | Class summaries at index time |
HYBRID_RERANK | Hybrid pool → LLM rerank | Chat API key |
Related MCP server: NetApp AIDE MCP Server
Install
cd zap-rag-mcp
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -r requirements.txtEnvironment
Variable | Required | Description |
| Yes | Absolute path to ZAP |
| Yes* | OpenAI-compatible embeddings base URL |
| Yes* | API key ( |
| Yes* | Must match model used when indexing |
| Rerank | Chat completions base |
| Rerank | Chat API key |
| Rerank | Chat model name |
| No | Default mode ( |
| No | Default top_k (10) |
| No | Scope to this project path |
| No |
|
* Falls back to OPENAI_BASE_URL / OPENAI_API_KEY if set.
Find the DB path in IntelliJ: Settings → ZAP → Database path.
Run
$env:ZAP_DB_PATH = "C:\path\to\rag.db"
$env:ZAP_EMBEDDING_BASE_URL = "http://127.0.0.1:11434/v1"
$env:ZAP_EMBEDDING_API_KEY = "ollama"
$env:ZAP_EMBEDDING_MODEL = "nomic-embed-text"
python server.pyMCP over stdio (no HTTP port).
MCP host config (Kilo / Cursor / Claude Desktop)
See mcp.example.json. Example:
{
"mcpServers": {
"zap-rag": {
"command": "C:\\path\\to\\zap-rag-mcp\\.venv\\Scripts\\python.exe",
"args": ["C:\\path\\to\\zap-rag-mcp\\server.py"],
"env": {
"ZAP_DB_PATH": "C:\\path\\to\\rag.db",
"ZAP_EMBEDDING_BASE_URL": "http://127.0.0.1:11434/v1",
"ZAP_EMBEDDING_API_KEY": "ollama",
"ZAP_EMBEDDING_MODEL": "nomic-embed-text"
}
}
}
}Agent skill
See .grok/skills/searching-zap-rag/SKILL.md (Anthropic Agent Skills: third-person description, progressive references/) for how coding agents should call the tools.
Related
IntelliJ plugin (indexing + chat UI): intellij-code-rag-plugin
License
Apache-2.0
This server cannot be deployed
Maintenance
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