AI Research
Cartograph: Federated Tool Discovery with Operator-Attested Retrieval for AI Agents
Scaling agentic tool discovery through federated proxy architecture.
The Model Context Protocol (MCP) enables AI agents to discover and call tools, but loading every definition becomes expensive as connected catalogs grow. We present Cartograph, a federated MCP proxy that changes agent-visible tool discovery from $O(n)$ catalog traversal to $O(k)$...
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ArXiv CS.CL
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2 min
ArXiv CS.CL
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Cartograph optimizes the agentic workflow by replacing inefficient linear catalog scanning with a federated retrieval system. This transition to O(k) complexity is a critical step toward enabling AI agents to operate across massive, ecosystem-wide tool libraries without incurring prohibitive performance costs.
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