arXiv 2606.13663v1 introduces HyperTool, a method for "compiling" MCP (Model Context Protocol) tool calls into a single piece of code. The standout: Qwen3 Agents using HyperTool see their accuracy roughly double on complex multi-tool tasks, with no quality loss on simpler tasks.
The "MCP tool call" problem: MCP is the standard for AI tool integration, and MCP tool calls are simple "call function X with arguments Y" operations. For complex multi-tool tasks (e.g., "search the web, summarize the results, post to Slack, update the database"), the Agent must make 10-20 sequential tool calls, with each call being a separate round-trip. This is slow and error-prone.
The HyperTool fix: HyperTool "compiles" multiple tool calls into a single piece of code, executed in a sandbox. The Agent writes a Python script that calls the tools in sequence, and the sandbox executes the script and returns the result. The result is 5-10× faster (single script execution vs multiple round-trips) and more accurate (the Agent can compose tools in ways that are hard to express as sequential calls).
The benchmark: on the "complex multi-tool" Agent benchmark, HyperTool-augmented Qwen3 Agents score 2× the baseline. On the "simple single-tool" benchmark, the scores are unchanged. The "code compilation" pattern works for complex tasks without hurting simple tasks.
The bigger takeaway: "tool compilation" is the right approach for complex Agent tasks. The "one tool call at a time" assumption is wasteful, and the "compile to code" approach is significantly more efficient. For the industry, this means Agent frameworks will move to "tool compilation" as a first-class feature, and the next round of Agent efficiency improvements will come from this direction.