token-pilot
MCP server that reduces token consumption in AI coding assistants by up to 90% via structural reads, PreToolUse hooks, and tp-\* subagents.
README
Token Pilot
Token-efficient AI coding, enforced. Cuts context consumption in AI coding assistants by up to 90% without changing the way you work.
Three layers, each useful on its own, stronger together:
- MCP tools — structural reads (
smart_read,read_symbol,read_for_edit, …). Ask for an outline or load one function by name instead of the whole file. - PreToolUse hooks — intercept heavy native tool calls (
Readon large files, recursiveGrep, unboundedgit diff) and redirect to token-efficient alternatives. tp-*subagents — Claude Code delegates with MCP-first behaviour and tight response budgets.
How It Works
Traditional: Read("user-service.ts") → 500 lines → ~3000 tokens
Token Pilot: smart_read("user-service.ts") → 15-line outline → ~200 tokens
read_symbol("UserService.updateUser") → 45 lines → ~350 tokens
After edit: read_diff("user-service.ts") → ~20 tokens
Files under 200 lines are returned in full — zero overhead for small files.
Benchmarks
Measured on public open-source repos. Files ≥50 lines only:
| Repo | Files | Raw Tokens | Outline Tokens | Savings |
|---|---|---|---|---|
| token-pilot (TS) | 55 | 102,086 | 8,992 | 91% |
| express (JS) | 6 | 14,421 | 193 | 99% |
| fastify (JS) | 23 | 50,000 | 3,161 | 94% |
| flask (Python) | 20 | 78,236 | 7,418 | 91% |
| Total | 104 | 244,743 | 19,764 | 92% |
smart_readoutline savings only. Real sessions additionally benefit from session cache,read_symbol, andread_for_edit. Reproduce:npx tsx scripts/benchmark.ts.
Quick Start
npx -y token-pilot init
Creates (or merges into) .mcp.json with token-pilot + context-mode, then prompts to install tp-* subagents. Restart your AI assistant to activate.
What You Get
- 22 MCP tools — structural reads, symbol search, git analysis, session analytics → tools reference
- PreToolUse hooks — block heavy
Grep/Bash/Readcalls; redirect to efficient alternatives → hooks & modes - 25
tp-*subagents (Claude Code only) — MCP-first delegates with haiku/sonnet model tiers and budget enforcement → agents reference - Tool profiles — trim advertised
tools/listto save ~2 k tokens per session → profiles & config
Client Support Matrix
| Client | MCP tools | PreToolUse hooks | tp-* subagents |
|---|---|---|---|
| Claude Code | ✅ | ✅ | ✅ |
| Cursor | ✅ | ✅ | ❌ |
| Codex CLI | ✅ | ✅ | ❌ |
| Gemini CLI | ✅ | ✅ | ❌ |
| Cline (VS Code) | ✅ | ✅ | ❌ |
| Antigravity | ✅ | ✅ | ❌ |
Manual config snippets for each client → installation guide
Enforcement Mode
TOKEN_PILOT_MODE controls how aggressively Token Pilot redirects heavy native tool calls:
| Value | Behaviour |
|---|---|
advisory |
Allow all — hooks pass through, advisory notes only |
deny (default) |
Block heavy Grep/Bash patterns; intercept large Read calls |
strict |
Deny + auto-cap MCP output (smart_read ≤ 2 000 tokens, find_usages → list mode, smart_log → 20 commits) |
TOKEN_PILOT_MODE=strict npx token-pilot
Ecosystem
Token Pilot owns input tokens — the stuff Claude reads from files, git, search. The other half of a session (what Claude writes back, how it executes code, how it remembers state across days) is owned by separate tools. They compose cleanly:
| Tool | Owns | Typical savings |
|---|---|---|
| Token Pilot | code reads, git, search | 60-90% input |
| caveman | Claude's response prose (terse-speak skill) | ~75% output |
| ast-index | the structural indexer Token Pilot rides on | foundation |
| context-mode | sandboxed shell / python / js execution | 90%+ on big stdout |
A session that pairs token-pilot + caveman typically hits ~85-90% total reduction — each cuts a different half, no overlap. Install what you need; none of them assume the others are present.
Rules of thumb: read code → smart_read/read_symbol; execute code with big output → context-mode execute; bash-only agent → ast-index CLI. Never copy the whole stack into CLAUDE.md — Token Pilot's doctor warns when CLAUDE.md exceeds 60 lines.
Supported Languages
TypeScript, JavaScript, Python, Go, Rust, Java, Kotlin, C#, C/C++, PHP, Ruby. Non-code (JSON/YAML/Markdown/TOML) gets structural summaries. Regex fallback handles most other languages.
Update / New Machine
Claude Code (plugin — recommended):
# Install on a new machine:
claude plugin marketplace add https://github.com/Digital-Threads/token-pilot
claude plugin install token-pilot@token-pilot
# Update to latest:
claude plugin update token-pilot
Other clients (Cursor, Codex, Cline, …):
# Install on a new machine:
npx -y token-pilot init
# Update to latest — npx always pulls fresh, just restart your client.
# Or if installed globally:
npm i -g token-pilot@latest
npx token-pilot install-hook
npx token-pilot install-agents --scope=user --force
Tips for Claude Code 2.1.139+
The May 2026 Claude Code update changed a few things that affect how token-pilot is invoked. Nothing breaks on older versions — these are quality-of-life notes for the newer ones.
-
Run a tp-* agent directly without the
plugin:prefix.claude --agent tp-debugger "fix the stack trace"now works the same as--agent token-pilot:tp-debugger. The Task tool dispatcher resolves the short name automatically. -
Cold ast-index calls — raise
MCP_TOOL_TIMEOUT. The firstfind_usages/outline/read_symbolon a large repo triggers an index build. Default per-MCP-tool timeout (60 s) is enough for ~50k-file repos; bigger ones benefit fromMCP_TOOL_TIMEOUT=120000in~/.claude/settings.json. Subsequent calls hit the cache and return in ~50 ms. -
Background sessions with
--mcp-config. Dispatching a worker viaclaude agentsor--bgwith--mcp-config /path/to/other.jsonswaps the MCP set for that session. Iftoken-pilotis not in the override config, MCP tools (smart_read,find_usages, …) are unavailable in that worker even though the hooks (Read / Edit / Bash / Grep / Task) still fire — hooks are project-level, MCP tools are session-level. Addtoken-pilotto the override config or skip--mcp-config. -
claude plugin details token-pilot. Shows the projected per-turn token cost, the hook event names, and the MCP server entry. The skill list, the agent list, and the LSP list are all auto-discovered from the canonical sub-folders.
Troubleshooting
npx token-pilot doctor # diagnose: ast-index, config, upstream drift
# "ast-index not found" → npx token-pilot install-ast-index
# "hooks not firing" → restart your AI assistant
Credits
Built on ast-index · @ast-grep/cli · MCP SDK · chokidar
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。