synthelion 1.0.0

MCP plugin + Python library for LLM token compression. 50+ languages, zero ML models. Port of Caveman (C#).

Synthelion — Claude Code Plugin + Python Library

Synthelion is a Claude Code MCP plugin and Python library that reduces LLM token usage by stripping grammatical noise and lemmatizing words — across 50+ languages, with zero ML model dependencies.

"Why use many tokens when few tokens do trick?" — A caveman (and your wallet).

Python port of Caveman by Passaro Francesco Paolo (Digitalsolutions.it).

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Use as Claude Code plugin (30 seconds)

1. Install:

pip install synthelion

2. Add to Claude Code (~/.claude/settings.json on macOS/Linux, %APPDATA%\Claude\claude_desktop_config.json on Windows):

{
  "mcpServers": {
    "synthelion": {
      "command": "synthelion-mcp"
    }
  }
}

3. Restart Claude Code. Done — the tools compress, detect_language, route_content, summarize, compress_batch are now available.

Zero-install with uvx:

{
  "mcpServers": {
    "synthelion": {
      "command": "uvx",
      "args": ["synthelion-mcp"]
    }
  }
}

→ Full plugin guide: docs/claude-code-plugin.md

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Powered by Synthelion — © Passaro Francesco Paolo, Digitalsolutions.it (https://digitalsolutions.it)

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Installation

pip install synthelion
# With MCP server support (for Claude Code, OpenCode, …):
pip install "synthelion[mcp]"
# With OpenAI function tools:
pip install "synthelion[openai]"

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Quick start

from synthelion import CompressionService, CompressionLevel

svc = CompressionService()
result = svc.compress(
    "I would like to know if it is possible to receive information about cheap restaurants in Rome.",
    CompressionLevel.SEMANTIC,
)
print(result.compressed_text)       # "know possible receive information cheap restaurant Rome"
print(f"{result.efficiency_pct:.1f}% saved")

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Compression levels

Level	What it does	Typical savings
LIGHT	Remove stop words	~25–35%
SEMANTIC	Stop words + lemmatization	~30–69%
AGGRESSIVE	Lemmatization + generic-term pruning	~35–70%

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Language detection

from synthelion import LanguageDetector

det = LanguageDetector()
print(det.detect("Vorrei un tavolo per due persone, per favore."))  # ita
scores = det.detect_with_scores("Where is the nearest train station?")
# {"eng": 0.42, ...}

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Content-aware routing

from synthelion import ContentRouter, CompressionProfile

router = ContentRouter.from_profile(CompressionProfile.BALANCED)
result = router.route(content)   # auto-detects JSON/HTML/diff/log/code/prose
print(result.strategy_used, result.savings_pct)

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MCP server (Claude Code / OpenCode)

# Run the MCP server on stdio:
synthelion-mcp

# Or add to your Claude Code MCP config:
# {
#   "mcpServers": {
#     "synthelion": { "command": "synthelion-mcp" }
#   }
# }

Tools exposed: compress, detect_language, route_content, summarize, compress_batch.

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OpenAI function tools

from synthelion.plugins.openai_tools import get_tool_definitions, execute_tool

tools = get_tool_definitions()
# Pass to: client.chat.completions.create(tools=tools, ...)

# Execute a tool call returned by the model:
result = execute_tool("compress", {"text": "...", "level": "semantic"})

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CLI

synthelion compress --text "Hello world, I would like to know..." --level semantic
synthelion detect --text "Guten Morgen, wie geht es Ihnen?"
synthelion route --file myfile.json
synthelion serve-mcp   # same as synthelion-mcp

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Summarization

from synthelion.nlp import TfIdfSummarizer, TextRankSummarizer

summarizer = TfIdfSummarizer()
summary = summarizer.summarize(long_text, sentence_count=3)

tr = TextRankSummarizer()
summary = tr.summarize(long_text, ratio=0.3)

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Agent toolkit

from synthelion.agent import ContextWindow, MemoryStore

window = ContextWindow(max_tokens=4000)
window.append("user", "Tell me about Rome.")
window.append("assistant", "Rome is the capital of Italy...")
# Auto-compacts when over budget:
print(window.to_messages_json())

memory = MemoryStore()
memory.remember({"summary": "User prefers Italian cuisine", "keywords": ["pizza", "pasta"]})
relevant = memory.recall("What food does the user like?", top_k=3)

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Attribution

Synthelion is a Python port of Caveman — © 2026 Passaro Francesco Paolo, Digitalsolutions.it. Original C# source: https://github.com/francescopaolopassaro/caveman

Language data derived from Universal Dependencies treebanks (CC BY-SA / CC BY).