Symbol-level code indexer MCP server — token-efficient AI editing with confirm-before-read flow
Project description
code-outline-graph
Symbol-level code indexer and MCP server. Parses your codebase with tree-sitter, stores symbols in SQLite + vector DB, and exposes a confirm-before-read protocol so AI assistants read only the symbols they need — not whole files.
10x–50x fewer tokens compared to reading files directly.
Install
pip install code-outline-graph
Quick Start
cd your-project
code-outline-graph build .
build runs once and configures everything — index, MCP configs, hooks, skill. Output:
╔══════════════════════════════════════════════════════════╗
║ code-outline-graph • Building Index ║
╚══════════════════════════════════════════════════════════╝
[1/7] Indexing /home/user/myproject ...
SKIP .env (secret file)
WARN src/broken.py parse error line 42
OK src/auth/views.py 23 symbols 0.04s
OK src/api/routes.py 45 symbols 0.11s
src/auth/ → 3 files 67 symbols
src/api/ → 8 files 203 symbols
[████████████████████] 100% 186 files · 1789 symbols → Done!
Skipped: 1 • Errors: 1 • Time: 3.2s
[2/7] Writing Claude Code / Cursor MCP config (.mcp.json) ...
Written: /home/user/myproject/.mcp.json ✓
[3/7] Writing Codex CLI config + hooks ...
Written: .codex/config.toml ✓
Written: .codex/hooks.json ✓
[4/7] Writing Gemini CLI config + hooks ...
Written: .gemini/settings.json ✓
[5/7] Writing Claude Code SessionStart + PostToolUse hooks ...
Written: .claude/settings.json ✓
[6/7] Writing AI instruction blocks ...
Updated: AGENTS.md ✓
Updated: GEMINI.md ✓
[7/7] Installing Claude Code skill ...
Installed: SKILL.md ✓
Installed: examples.md ✓
══════════════════════════════════════════════════════════
Build complete in 5.1s
186 files • 1789 symbols • 1 skipped • 1 error
══════════════════════════════════════════════════════════
CLI Commands
| Command | Description |
|---|---|
code-outline-graph build [path] |
Index project + write MCP configs for all clients |
code-outline-graph update [path] |
Reindex changed files only |
code-outline-graph search <query> |
Search symbols by keyword |
code-outline-graph outline <file> |
List all symbols in a file |
code-outline-graph status [path] |
Show index stats |
code-outline-graph serve [path] |
Start MCP server (stdio) |
code-outline-graph install-skill |
Install Claude Code skill to ~/.claude/skills/ |
MCP Tools
The server exposes 9 tools to AI assistants:
| Tool | Description |
|---|---|
resolve_edit_target |
NL description → top-5 symbol candidates (signatures only, no body) |
read_symbol_body |
Read source lines for one symbol only |
list_outline |
All symbols in a file with line ranges |
get_outline_summary |
Compressed signatures-only outline |
get_file_header |
Imports + top-level constants only |
get_symbol |
Exact symbol metadata by name |
find_by_keyword |
Keyword search across all symbol names |
get_line_range |
Read arbitrary line slice from a file |
index_project |
Index a directory and start file watcher |
Confirm-Before-Read Protocol
1. resolve_edit_target({"description": "user login handler"})
→ [{name: "login", file: "views/auth.py", start: 45, end: 89, signature: "def login(...)"}]
2. AI picks correct candidate from signatures (no body read yet)
3. read_symbol_body({"name": "login", "file": "views/auth.py"})
→ 44 lines instead of 300-line file
Supported Languages
Python, JavaScript, TypeScript, TSX, Go, Rust, Java, C, C++, C#, Ruby, PHP, Swift, Kotlin, JSON, YAML, TOML, INI
Architecture
cli.py CLI entry point — build/update/search/outline/status/serve
server.py MCP server — 9 tools, file watcher lifecycle
indexer.py Orchestrates parse → checksum → DB upsert → embeddings
parser.py tree-sitter parsing → Symbol extraction per language
db.py SQLite + sqlite-vec — symbols table + FTS5 + vector index
search.py FTS search, keyword search, vector search, resolve_edit_target
watcher.py watchdog file watcher — debounced reindex + git HEAD tracking
embeddings.py fastembed vector embeddings for semantic search
paths.py Per-project DB path resolution (~/.cache/code-outline-graph/)
Each project gets its own SQLite DB at ~/.cache/code-outline-graph/<hash>/vectors.db. The watcher reindexes files on save and reindexes the whole project on git branch switches.
MCP Configuration
build auto-configures all supported clients in one shot:
| Client | MCP config | SessionStart hook |
|---|---|---|
| Claude Code / Cursor | .mcp.json |
.claude/settings.json |
| Codex CLI | .codex/config.toml |
.codex/hooks.json |
| Gemini CLI | .gemini/settings.json |
.gemini/settings.json |
It also appends usage instructions (sentinel-bounded, safe to re-run) to AGENTS.md and GEMINI.md so clients that read those files know to use the MCP tools.
The SessionStart hook runs code-outline-graph update . at the start of every AI session, keeping the index fresh without manual intervention.
Claude Code Skill
build automatically installs the Claude Code skill to ~/.claude/skills/code-outline-graph/ (SKILL.md + examples.md). The skill teaches Claude the confirm-before-read protocol and tool reference.
To install manually or update after upgrading:
code-outline-graph install-skill
Development
pip install -e ".[dev]"
pytest # run all tests
pytest tests/test_parser.py # run single test file
License
MIT
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