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New tool MCP RTK slashes AI token usage by 90%

By PulseAugur Editorial · [1 sources] ·

A new open-source tool called MCP RTK has been developed to significantly reduce token consumption when using AI models like Claude Code with external tools. The tool acts as a proxy, filtering unnecessary data from server responses before they reach the AI, thereby saving millions of tokens and reducing costs. MCP RTK employs an 8-step filtering process, including removing null fields, truncating long strings, and stripping technical metadata, with configurable presets for popular services like GitLab and Grafana. AI

IMPACT Reduces operational costs for AI developers by minimizing token usage in tool-augmented AI workflows.

RANK_REASON The item describes a new open-source tool that addresses a specific technical problem in AI model interaction.

Read on dev.to — MCP tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New tool MCP RTK slashes AI token usage by 90%

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29 / 100
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Tool
The item describes a new open-source tool that addresses a specific technical problem in AI model interaction.
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product, infra
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — MCP tag TIER_1 English(EN) · Thomas Tartrau ·

    MCP RTK: cut 90% of MCP server tokens

    <p>I use <a href="https://dev.to/blog/en/claude-code-setup-2026">Claude Code</a> every day for development. Like many developers, I've connected several MCP servers (GitLab, Grafana, Sentry...) to give Claude direct access to my tools. The problem: every MCP call injects tens of …

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