name: token-efficient description: "Use when processing 50+ items, analyzing CSV/log files, executing code in sandbox, or searching for tools. Load for data processing tasks. Achieves 98%+ token savings via in-sandbox execution, progressive disclosure, and pagination. Supports heredocs for multi-line bash." keywords: csv, logs, execute, sandbox, pagination, batch, filter, aggregate

Token-Efficient MCP

Process data in sandbox, return only results. 98%+ token savings.

Instructions

•Search for tool: search_tools("csv") (95% savings vs loading all)
•Process data in sandbox (never load raw to context)
•Use pagination for large files: offset, limit
•Return summaries, not raw data

Quick Commands

bash

# Process CSV with filter
scripts/process-csv.sh data.csv "price > 100"

# Search logs for errors
scripts/search-logs.sh app.log "ERROR|WARN"

# Execute code in sandbox
scripts/run-sandbox.sh script.py

Token Savings

Tool	Savings	Example
`execute_code`	98%+	Run Python without loading
`process_csv`	99%	10K rows → 100 results
`process_logs`	95%	100K lines → 500 matches
`search_tools`	95%	Find tools on-demand

MCP Tools

Tool	Purpose
`execute_code`	Python/Bash/Node in sandbox
`process_csv`	Filter, aggregate CSV
`process_logs`	Pattern match logs
`search_tools`	Find tools by keyword
`batch_process_csv`	Multiple CSVs at once

References

File	Load When
references/patterns.md	Choosing which tool
references/examples.md	Need code examples