[Submitted on 13 Sep 2026]
Title:Cartograph: Federated Tool Discovery with Operator-Attested Retrieval for AI Agents
View a PDF of the paper titled Cartograph: Federated Tool Discovery with Operator-Attested Retrieval for AI Agents, by Justice Owusu Agyemang and 5 other authors
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Abstract: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 $O(k)$ progressive disclosure. Cartograph combines three mechanisms: (1) operator-attested capability cards, Ed25519-signed descriptions generated under the deploying operator's control rather than ranked publisher copy; (2) Rift, a three-layer confusable-cluster analysis comprising density clustering, query-margin analysis, and token diagnosis; and (3) two-stage retrieval, which ranks servers before tools. On a 22-server, 374-tool deployment, Cartograph exposes three proxy tools instead of 374 definitions. A 49-query author-constructed benchmark yields R@5 of 0.816, compared with 0.592 for a Jaccard keyword baseline, while a measured top-5 discovery exchange uses 475 tokens rather than 42,450 under the stated full-catalog accounting. Rift identifies 49 confusable clusters, including four HIGH-risk clusters in bootstrap-generated cards. An exploratory comparison of 119 LLM-generated descriptions removes the observed zero-distance cluster but shows that mixing card-generation regimes can reduce R@5. Gateway measurements over ten trials add 5ms mean latency (0.8%) relative to direct stdio MCP calls. Cartograph is complementary to code-execution approaches: it controls which tool descriptions are surfaced and records the provenance of the descriptions used for ranking for each query.
Subjects:
Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2609.30293 [cs.CL]
(or arXiv:2609.30293v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2609.30293
arXiv-issued DOI via DataCite
Submission history
From: Justice Owusu Agyemang [view email] [v1] Sun, 13 Sep 2026 09:07:29 UTC (35 KB)
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