MCP Servers

token-optimization-mcp

A fully offline MCP server for token estimation, prompt compression, model routing, and semantic caching to optimize LLM usage costs and efficiency.

README

token-optimization-mcp v0.2.0

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

Recommended Servers

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official

Featured

TypeScript

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official

Featured

Local

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official

Featured

TypeScript

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official

Featured

Python

E2B

Using MCP to run code via e2b.

Official

Featured

Neon Database

MCP server for interacting with Neon Management API and databases

Official

Featured

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official

Featured