清理工具

1. Install proxy

From PyPI (proxy + pruners):

uv tool install 'clear-your-tools[all]'

Quick start

Requires uv tool. Install uv

Optional (recommended):

uv run cyt setup ```

Stats are stored in ~/.config/cyt/stats.db by default.

---

Pruning pipeline

Tool Recommendations:

- Getting started / no setup — the default bm25 pipeline works out of the box with no remote API keys. - 50+ tools — run cyt setup and use rerank or llm. Rerank can be pipelined into LLM as a second stage (pipeline: [rerank, llm]) for stronger tool-level filtering on large catalogs.

Pipeline & Model Recommendations: Choose your pipeline based on model cost:

• Expensive models (≥$3/M input tokens, e.g. Sonnet): Use an LLM pruner pipeline.
• Cheap models ($0.10–$1/M input tokens, e.g. Haiku, Gemini 3 Flash): Use a rerank pipeline with a low-cost model.
• Premium models (e.g. Opus): Use an LLM pruner + rerank combined pipeline.

---

FAQ

<details> <summary><strong>Doesn't pruning burn more tokens than it saves?</strong></summary>

The default is BM25 algorithm running locally on your computer it is free. The reranker and weak LLM used for pruning are much cheaper per token than the main model (e.g. Claude Sonnet). You may spend extra tokens on pruning, but they cost a fraction of what you save on the main request. Set input_cost_per_token and output_cost_per_token in ~/.config/cyt/config.yaml to track savings.

Example pricing (input tokens):

The weak models such as Mercury 2 or GPT-OSS-120B returns only the IDs of tools to keep, so its output stays extremely small. Rerankers do not count output tokens and are usually much cheaper than a strong LLM.

Rule of thumb: saving 1M Sonnet input tokens is still worthwhile even if pruning uses up to ~10M Mercury tokens — roughly a 1:10 cost ratio. The reranker has roughly a 1:60 cost ratio.

In practice, pruning usually adds modest overhead. Worst case (no tools pruned), you might pay ~$3.30 instead of $3.00. With typical pruning (40–95% of tool tokens removed), tool-schema cost drops from ~$3.00 to roughly $0.15–$1.80, plus ~$0.30 for pruning — about $0.45–$2.10 total for tool-related cost, or roughly 30–85% savings depending on policy. </details>

<details> <summary><strong>Why don't I see 30–85% savings on my total request?</strong></summary>

Those numbers apply to tool schemas only of the input tokens only, not the full prompt (system message, conversation history, user message, etc.). Clear Your Tools prunes tools based on the user request; the rest of the request is unchanged. Codex agent has an efficient tool use and CYT saves less tokens.

How much you save overall depends on:

- How many tools you have — more MCP servers mean a larger share of the request is tool schemas. We do not recommend using CYT below 50 tools. - Which pruning policy you use — see Pruning policies.

To estimate savings on a captured request JSON, see DEV.md. To see statistics of actual net savings (input tokens) run:

uv run cyt stats totals

With ~100 tools and prune_all, expect ~85–95% savings on tool tokens and typically ~30%+ savings on the full request. The more tools you have the more overall savings you'll see.

</details>

<details> <summary><strong>Where can I see how many tools and parameters an MCP server has?</strong></summary>

The popular Fetch MCP server is a good example. On its Tools tab: 4 tools, each with 4 parameters (1 required, 3 optional) — 16 parameters total.

If the user asks to "fetch the Markdown of a webpage", the prune_all typically keeps only the Fetch Markdown tool with its required parameter plus any optional parameters that look relevant. Unrelated tools (e.g. Read file) are dropped entirely.

</details>

<details> <summary><strong>Is my provider/model supported?</strong></summary>

CYT's pruner models (the cheap reranker and LLM that decide which tools to keep) call providers through LiteLLM. If LiteLLM supports your provider and model, you can use them in CYT.

When you run cyt setup and add a pruner model, you'll be prompted for:

- Provider — LiteLLM provider route, without a trailing slash (e.g. openai, openrouter). - Model name — LiteLLM model string (see the provider docs). - API key env var — the name of the environment variable that holds your key, not the key itself (e.g. OPENAI_API_KEY, OPENROUTER_API_KEY). - domain_match — hostname from the provider's API base URL (e.g. openai.com for OpenAI, openrouter.ai for OpenRouter). Used to match outgoing requests to the right model config.

</details>

<details> <summary><strong>Claude Code reports ZlibError when using the proxy</strong></summary>

Install missing zlib:

npm install -g zlib
brew install zlib

This usually means the proxy returned a Content-Encoding: gzip (or deflate) header with a body that was already decompressed. Claude Code’s fetch then tries to inflate plain JSON/SSE and fails. It is not a missing zlib install on your machine or in CYT.

Fix: upgrade to a cyt build that streams upstream bytes unchanged (aiter_raw pass-through). After upgrading, verify:

curl --raw -sS -D - -o /tmp/cyt-msg.body \
  -H 'Accept-Encoding: gzip' \
  ... # your POST to http://127.0.0.1:8834/anthropic/v1/messages
head -c 4 /tmp/cyt-msg.body | xxd   # should show 1f8b when header says gzip

Also check: ANTHROPIC_BASE_URL must use http:// for the default plain-HTTP server, e.g. http://localhost:8834/anthropic. Using https:// against cyt proxy (without TLS/http2.serve) causes uvicorn’s Invalid HTTP request received and broken API calls.

</details>

<details> <summary><strong>Uvicorn logs Invalid HTTP request received</strong></summary>

cyt proxy listens for HTTP/1.1 on the configured port (default 8834). This warning almost always means a client connected with the wrong protocol:

• https://localhost:8834 while the proxy is plain HTTP → TLS handshake bytes, not HTTP
• HTTP/2 prior knowledge to uvicorn (use http2.serve + TLS certs only if you intend HTTPS)

Use http://localhost:8834/anthropic unless you have enabled Hypercorn TLS in config.

</details>

<details> <summary><strong>Should I use .env</strong></summary>

We strongly recommend using password vaults like macOS KeyChain

```shell