name: mcp-daemon-isolation description: Context isolation for query-type MCP tools (LSP, search, database) via external CLI. Use when MCP query results consume too many context tokens. allowed-tools: ["Read", "Bash", "Grep", "Glob"]
MCP Daemon Isolation for Query-Type MCPs
External CLI pattern for isolating query-type MCP tool results from main context.
Query-Type MCP 정의
| Type | Examples | 특징 |
|---|---|---|
| Query-type | Serena (LSP), Database, Search | 결과 크기 예측 불가, 수천 토큰 가능 |
| Action-type | File write, Git, Deploy | 결과 작음, 성공/실패 위주 |
식별 기준: find_*, search_*, get_*, list_* 패턴 도구
Problem
Claude Session
├── mcp__serena__find_symbol("UserService")
│ └── Result: 2,500 tokens (full JSON) ← CONSUMED
└── Context budget: rapidly depleting
Daemon isolates tool definitions (~350 tokens × tools), but results still consume context.
Solution: External CLI + Structured Extraction
Claude Session
├── Bash: serena-query find_symbol UserService
│ └── stdout: "• UserService [Class] @ src/user.py:42"
│ (~50 tokens) ← MINIMAL
└── Full result stored: /tmp/serena-result.json
Key insight: Claude IS the LLM. Structured extraction provides 95%+ token savings.
Architecture
┌──────────────┐ ┌──────────────────┐ ┌──────────────┐
│ Claude │────▶│ serena-query │────▶│ Serena │
│ Session │ │ (external CLI) │ │ Daemon :8765 │
└──────────────┘ └──────────────────┘ └──────────────┘
Bash (~50 tok) SSE + MCP Protocol 29 tools
For protocol details: Read("references/mcp-sse-protocol.md")
Structured Extractors
| Tool | Full JSON | Extracted Output | Savings |
|---|---|---|---|
list_dir | ~800 | 📁 Dirs(12): hooks... 📄 Files(11) | 95% |
get_symbols_overview | ~1,200 | Class(2): Config... Function(5) | 96% |
find_symbol | ~2,000 | • UserService [Class] @ src/user.py:42-98 | 97% |
search_for_pattern | ~1,500 | Matches(15) in 8 files | 95% |
For formatter code: Read("references/extractors-and-examples.md")
Usage
Output Modes
serena-query find_symbol UserService # summary (기본)
serena-query find_symbol UserService --mode location # 위치만 (Read 연계)
serena-query find_symbol UserService --mode full # 전체 JSON
Basic Commands
serena-query list_dir .
serena-query get_symbols_overview src/main.py --depth 1
serena-query find_symbol UserService --path src/
serena-query search_for_pattern "class.*Service" --path src/
serena-query find_symbol UserService --output /tmp/result.json
최적 워크플로우: 탐색-위치-읽기
1. 탐색 (--mode summary) ~25 토큰 "어떤 심볼이 있지?"
2. 위치 (--mode location) ~15 토큰 "정확히 어디있지?"
3. 읽기 (Read 도구) 실제 크기 필요한 코드만
| 시나리오 | stdio 방식 | daemon+Read | 절감률 |
|---|---|---|---|
| 클래스 분석 | ~525 | ~240 | 54% |
| 11개 함수 분석 | ~4,300 | ~665 | 85% |
| 대규모 검색 | ~10,000+ | ~500 | 95% |
For detailed examples: Read("references/extractors-and-examples.md")
Installation
pip install httpx
cp scripts/serena-query ~/.local/bin/
chmod +x ~/.local/bin/serena-query
Daemon Setup
uvx --from git+https://github.com/oraios/serena \
serena start-mcp-server --transport sse --port 8765 --project-from-cwd
Decision: Structured vs LLM Summarization
| Aspect | LLM Summarization | Structured Extraction |
|---|---|---|
| Latency | +2-5 seconds | ~0ms |
| Cost | API call per query | Zero |
| Consistency | Variable | Deterministic |
Claude IS the LLM consuming the output - no need for additional summarization.
격리 전략 가이드
| 시나리오 | 권장 | 이유 |
|---|---|---|
| 단일 심볼 편집 | stdio | 즉각적인 수정 |
| 코드베이스 탐색 | daemon | 대량 결과 예상 |
| 참조 추적 | daemon + location | 위치만 필요 |
| 리팩토링 계획 | daemon + full | 전체 구조 분석 |
Common Issues
| 증상 | 원인 | 해결 |
|---|---|---|
| "Received request before initialization" | 핸드셰이크 누락 | initialize → notifications/initialized → tools/call 순서 |
| "Connection refused on 8765" | Daemon 미실행 | systemctl --user start serena-daemon |
| "Empty result" | 구조 불일치 | --output으로 raw JSON 저장 후 확인 |