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token-saver-mcp

An MCP server plugin for Claude Code that automatically reduces token usage across your sessions. All optimizations are purely algorithmic — no extra API calls, no added cost.

Tools

Tool

What it does

compress_text

Strips comments (//, /* */, #, <!-- -->), blank lines & whitespace from code/prose. String-aware: never corrupts URLs, #hashtag/#fff hex colors, or markers inside string literals; comments inside template-literal ${} expressions are stripped

smart_read_file

Reads only relevant sections of a file. Structure-aware across JS/TS, Python, Go, Rust, Java & C#: returns the complete enclosing function/class/interface around keyword matches, with a configurable fallback window. Rejects binary files

summarize_output

Truncates long command output / logs to a token budget. Preserves error/failure lines anywhere in the output, keeps head + tail, collapses duplicate lines

summarize_diff

Compacts a unified git diff: keeps file headers, hunk headers & changed lines; strips context lines and index/mode noise. Renames and binary files are annotated

count_tokens

Counts token usage for any text (cl100k_base encoding)

generate_claudeignore

Generates a .claudeignore covering Node, Python, Rust, Go, Java, Ruby, PHP & Terraform artifacts plus modern tooling caches (Turbo, Vercel, Nuxt, SvelteKit, Storybook), seeded from your existing .gitignore

optimize_prompt

Rewrites verbose prompts to be concise (~40 filler-phrase rules). Fenced code blocks and inline code are passed through untouched

All tools return plain text with a compact stats footer — results are deliberately not JSON-wrapped, since JSON escaping of newlines and quotes would inflate the very token count this server exists to reduce.

Note on token counts: the server uses the cl100k_base encoding (via tiktoken), which is OpenAI's tokenizer. Claude's tokenizer differs, so all counts are approximations — typically within ~10–20% of Claude's actual usage. Relative savings percentages are unaffected.

Related MCP server: Ollama MCP Server

Benchmark results

Measured against real code fixtures and realistic prompt inputs. See benchmark/BENCHMARK.md for full methodology.

Tool

Avg token reduction

Best case

compress_text

31%

53% on JS with JSDoc

smart_read_file

44%*

81% extracting one function from a module

summarize_output

76%

84% on long build output

summarize_diff

50%

53% on a multi-file diff with renames

optimize_prompt

28%

52% on heavily padded prompts

count_tokens

accuracy tool — no reduction metric

generate_claudeignore

structural correctness tool — no reduction metric

* the smart_read_file average includes tiny synthetic fixtures used as multi-language correctness tests; on realistic files it ranges 38–81%.

Run the benchmark yourself:

npm run benchmark

Installation

1. Clone and install

git clone <your-repo-url> token-saver-mcp
cd token-saver-mcp
npm install

2. Add to Claude Code

claude mcp add token-saver -- node /absolute/path/to/token-saver-mcp/src/index.js

Or manually edit ~/.claude.json under mcpServers:

{
  "mcpServers": {
    "token-saver": {
      "command": "node",
      "args": ["/absolute/path/to/token-saver-mcp/src/index.js"]
    }
  }
}

3. Verify

claude mcp list

You should see token-saver listed as connected.


Usage examples

Use smart_read_file on src/api/routes.js, focus on "authentication" and "middleware"
Generate a .claudeignore for my project at /home/user/myapp and write it to disk
Count tokens in this output: [paste output]
Compress this before sending: [paste code]
A
license - permissive license
-
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

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