CRAG-MCP

CRAG-MCP

A Model Context Protocol server that builds and queries a config-aware code graph with support for conditional compilation (#ifdef) filtering, enabling context-aware code analysis across different build configurations.

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README

CRAG-MCP: Config-Aware Code Graph via MCP

程式碼 graph 建構與查詢 MCP Server,支援條件編譯(#ifdef)動態過濾。 每個 workspace 獨立儲存 graph + config,支援多專案比較。

核心概念:Config-Aware Graph

傳統 Graph:
  cfg80211_p2p_init() ──→ cfg80211_get_bss()
  (不知道這個 function 需要什麼條件才能存在)

CRAG Graph:
  cfg80211_p2p_init()
    active_conditions: {"WIFI_P2P_SUPPORT": "y"}
    ──→ cfg80211_get_bss()
  
  Query: preprocess_config({"WIFI_P2P_SUPPORT": "n"})
  Result: cfg80211_p2p_init() 被自動過濾掉
  
  Query: preprocess_config({"WIFI_P2P_SUPPORT": "y"})
  Result: cfg80211_p2p_init() 出現

架構

crag-mcp/
├── crag_mcp/
│   ├── core/
│   │   ├── workspace.py          # Workspace 掃描
│   │   └── config_context.py     # Config / #ifdef 管理
│   ├── parsers/
│   │   └── tree_sitter_parser.py # AST + #ifdef 條件提取
│   ├── llm/
│   │   └── small_llm.py           # Semantic analysis
│   ├── graph/
│   │   └── kuzu_graph.py         # Kùzu + active_conditions
│   └── server/
│       └── mcp_server.py         # 7 tools
├── pyproject.toml
└── README.md

MCP Tools (7)

Tool 用途
configure(workspace_path?, small_llm?) 設定 workspace 與 LLM
preprocess_config(config_path?, define_overrides?, workspace_path?) 載入條件編譯設定(綁定 workspace)
query_graph(query, max_results?, workspace_path?) 搜尋(自動套用 config 過濾)
get_callers(func, depth?, workspace_path?) Graph: upstream(config-aware)
get_callees(func, depth?, workspace_path?) Graph: downstream(config-aware)
get_call_path(A, B, workspace_path?) Graph: path(config-aware)
graph_stats(workspace_path?) Graph 狀態

所有查詢 tool 都接受 workspace_path 參數,指向要操作的 workspace。 不傳則用最後一次 configure() 設定的 workspace。

Atomic 設計哲學

每個 workspace 完全獨立,各自擁有自己的:

/ws/A/.crag-mcp/
├── graph.kuzu/           # Kùzu DB(函式 + 呼叫關係)
└── file_cache/           # parse cache
  • query_graph(ws=A) 只查 A 的 DB、只套 A 的 config
  • query_graph(ws=B) 只查 B 的 DB、只套 B 的 config
  • 兩者完全不會互相干擾

Agent(或 LLM)負責 orchestration — 輪流查不同 workspace,再自行比較結果。

使用流程

1. 一般專案(無 #ifdef)

configure(workspace_path="/path/to/project")
query_graph("authentication flow")
# 無條件過濾,所有 code 都出現

2. C / Linux Kernel(有 #ifdef)

configure(workspace_path="/path/to/linux")
preprocess_config(
    config_path="/path/to/linux/.config",
    define_overrides={"WIFI_P2P_SUPPORT": "y"}
)
query_graph("WIFI P2P implementation")
# 只有 WIFI_P2P_SUPPORT=y 的 code 會出現

# 改 config,重新查詢
preprocess_config(
    config_path="/path/to/linux/.config",
    define_overrides={"WIFI_P2P_SUPPORT": "n"}
)
query_graph("WIFI P2P implementation")
# P2P 相關 code 被自動過濾掉

3. 多 Workspace 比較(Agent 層次)

configure(workspace_path="/ws/A")
preprocess_config(config_path="/ws/A/.config", workspace_path="/ws/A")

configure(workspace_path="/ws/B")
preprocess_config(config_path="/ws/B/.config", workspace_path="/ws/B")

result_a = query_graph("wifi p2p flow", workspace_path="/ws/A")
result_b = query_graph("wifi p2p flow", workspace_path="/ws/B")

# Agent 自行比較,再決定要不要查 C
result_c = query_graph("wifi p2p flow", workspace_path="/ws/C")

preprocess_config 支援的格式

格式 範例 說明
Linux .config CONFIG_WIFI=y 自動 parse
C Header #define WIFI 1 #define 提取
Makefile CFLAGS += -DWIFI=1 -D 提取
JSON {"WIFI": "y"} 直接載入
Manual define_overrides={} 程式設定

Config 過濾邏輯

# Graph node 儲存
{
    "name": "cfg80211_p2p_init",
    "active_conditions": {"WIFI_P2P_SUPPORT": "y"}
}

# Query 時比對
preprocess_config(define_overrides={"WIFI_P2P_SUPPORT": "n"})
# → cfg80211_p2p_init 被過濾(條件不滿足)

preprocess_config(define_overrides={"WIFI_P2P_SUPPORT": "y"})
# → cfg80211_p2p_init 出現(條件滿足)

# 無 active_conditions → 永遠出現(always active)

本地儲存位置

每個 workspace 會在自己的根目錄下建立 .crag-mcp/ 目錄:

/path/to/project/.crag-mcp/
├── graph.kuzu/           # Kùzu DB(二進制目錄)
└── file_cache/           # parse cache(JSON)

加到 .gitignore

.crag-mcp/

安裝

cd /path/to/crag-mcp/
pip install -e .

或使用 uv

cd /path/to/crag-mcp/
uv pip install -e .

OpenCode 設定

{
  "mcpServers": {
    "crag": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/crag-mcp", "-m", "crag_mcp.server.mcp_server"],
      "env": {
        "CRAG_WORKSPACE": "${workspaceFolder}",
        "CRAG_SMALL_LLM": "gemma4:31b-cloud"
      }
    }
  }
}

Agent 決策流程

Agent 看到專案:
├── 有 .config / Kconfig / #ifdef → 呼叫 preprocess_config()
├── 純 Python / JS / Go → 不呼叫(無條件編譯)
└── 使用者提到 "kernel" / "config" → 詢問是否 preprocess

Token 節省

場景 傳統 CRAG-MCP
Kernel query 餵全部 code(含 dead code) 只查 active code
Config 切換 重新 index 整個 repo 只改 query 條件
#ifdef 分析 LLM 自己猜條件 graph 標記清楚

License

MIT

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