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Compress MCP tool schemas to cut tokens while preserving semantics deterministically.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Refract" yet — see the docs or source repo.
Connect my MCP tool service to the Refract proxy, compress all tool schemas dynamically, and explain how to reduce prompt token costs without changing tool logic.
An integration plan showing how Refract compresses schemas, reduces token usage, and preserves tool behavior and meaning.
I have a workflow with twenty MCP tools. Design an integration approach using Refract and assess its impact on context length, response stability, and tool-calling efficiency.
Optimization recommendations for a multi-tool setup, including proxy deployment, expected token savings, and stability considerations.
Explain how Refract verifies 100% signal preservation after compressing MCP tool schemas, and provide a testing and acceptance checklist for an engineering team.
A validation explanation and test checklist to help the team confirm the compressed output is usable, deterministic, and safe for tool calling.
Compress long contexts and retrieve reusable summaries to reduce LLM token usage.
Compress prompts, tool outputs, and replies to reduce LLM token costs.
Compresses LLM conversation context while preserving meaning and reducing token usage.
Groups OpenAPI operations and trims schemas to improve MCP tool selection.
Compress content through MCP to reduce context size in AI workflows.
Proxy multiple MCP servers while reducing token usage with on-demand tool loading.