Token Optimization

Production-ready Model Context Protocol server for token counting, prompt compression, model routing and semantic caching. Zero external API calls — works fully offline.

Tools

Tool	Description
estimate_tokens	Count tokens for any text+model (calibrated chars/token ratios)
compress_prompt	Shrink prompts with trim, summarize_hint or aggressive strategy
route_model	Pick cheapest model meeting quality + context requirements
cache_lookup	Semantic cache hit/miss by prompt or pre-computed key
cache_store	Store prompt+result with token-savings metadata
cache_invalidate	Remove one or all cache entries
analyze_context	Conversation health: role breakdown, issues, recommendations
savings_report	Session-level token/USD savings dashboard
deduplicate_messages	Remove duplicate turns, count saved tokens

Quick Start

cd mcps/token-optimization-mcp
uv sync

# stdio – Claude Code / Copilot
uv run main.py

# SSE – LangGraph / CrewAI / browser
uv run main.py --sse --port 8001

Environment Variables

Variable	Default	Description
USE_REDIS	false	Enable Redis backend
REDIS_URL	redis://localhost:6379/1	Redis connection URL
CACHE_TTL_SECONDS	86400	Default cache TTL (1 day)
RATE_LIMIT_PER_MIN	120	Requests/min per client
AUDIT_LOG_ENABLED	true	Print audit log to stdout

Registration

Claude Code (~/.claude/settings.json)

{
  "mcpServers": {
    "token-optimization": {
      "command": "uv",
      "args": ["run", "/path/to/token-optimization-mcp/main.py"]
    }
  }
}

VS Code Copilot (.vscode/mcp.json)

{
  "servers": {
    "token-optimization": {
      "type": "stdio",
      "command": "uv",
      "args": ["run", "${workspaceFolder}/mcps/token-optimization-mcp/main.py"]
    }
  }
}

SSE (LangGraph / CrewAI / Cursor)

http://127.0.0.1:8001/sse

Supported Models (routing catalogue)

Model	Context	Quality	Cost/1k
github:copilot	128k	8	free
gpt-4o-mini	128k	7	$0.00015
claude-3-5-haiku	200k	7	$0.00025
gemini-1.5-flash	1M	6	$0.000075
gpt-4o	128k	9	$0.005
claude-3-5-sonnet	200k	9	$0.003
claude-3-opus	200k	10	$0.015

Testing

uv run --group test pytest
# 118 tests, 100% coverage

Architecture

token-optimization-mcp/
├── main.py                      ← FastMCP server (9 tools)
├── pyproject.toml
├── README.md
├── tests/
│   ├── conftest.py              ← state-reset fixtures
│   ├── test_helpers.py          ← unit tests + Hypothesis
│   └── test_tools.py            ← integration tests per tool
└── mcp-servers/
    └── context-cache-server/    ← standalone Redis-backed sub-server
        ├── server.py
        ├── config.py
        └── security.py