{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:6SNOTFM4XJRHKR4TZNU3CIIOJO","short_pith_number":"pith:6SNOTFM4","schema_version":"1.0","canonical_sha256":"f49ae9959cba62754793cb69b1210e4b9e707ba39ed141aeea0daf2cc54cb3bf","source":{"kind":"arxiv","id":"2506.01056","version":4},"attestation_state":"computed","paper":{"title":"MCP-Zero: Active Tool Discovery for Autonomous LLM Agents","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SE"],"primary_cat":"cs.AI","authors_text":"Hao Feng, Xiang Fei, Xiawu Zheng","submitted_at":"2025-06-01T15:48:53Z","abstract_excerpt":"True intelligence requires active capability acquisition, yet current LLM agents inject pre-defined tool schemas into prompts, reducing models to passive selectors and falling short of robust general-purpose agency. We introduce MCP-Zero, an active agent framework that restores tool discovery autonomy to LLMs themselves. Instead of overwhelming models with all available tools, MCP-Zero enables agents to actively identify capability gaps, and request specific tools on-demand, transforming them from large-scale retrievers into genuine autonomous agents. The framework operates through three core "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.01056","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-06-01T15:48:53Z","cross_cats_sorted":["cs.SE"],"title_canon_sha256":"28ac56c64b21f5a6ee32bae8ec75bc789b1027f296c8f79882597568db66c821","abstract_canon_sha256":"bcf11bb89bdc86fc69e25d9e33db8513f41b0c65f8e259def351422b1f8f9b61"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:26:05.007548Z","signature_b64":"fzAOuJ7qD87HbPsmpqMiE9pXAq0YQkYydIL3O7r+z+UkwrsiXTtP8nDQMj6nIrinQ0O5ekjdeATh4oLm3mYCCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f49ae9959cba62754793cb69b1210e4b9e707ba39ed141aeea0daf2cc54cb3bf","last_reissued_at":"2026-07-05T11:26:05.007093Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:26:05.007093Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MCP-Zero: Active Tool Discovery for Autonomous LLM Agents","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SE"],"primary_cat":"cs.AI","authors_text":"Hao Feng, Xiang Fei, Xiawu Zheng","submitted_at":"2025-06-01T15:48:53Z","abstract_excerpt":"True intelligence requires active capability acquisition, yet current LLM agents inject pre-defined tool schemas into prompts, reducing models to passive selectors and falling short of robust general-purpose agency. We introduce MCP-Zero, an active agent framework that restores tool discovery autonomy to LLMs themselves. Instead of overwhelming models with all available tools, MCP-Zero enables agents to actively identify capability gaps, and request specific tools on-demand, transforming them from large-scale retrievers into genuine autonomous agents. The framework operates through three core "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01056","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2506.01056/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.01056","created_at":"2026-07-05T11:26:05.007152+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.01056v4","created_at":"2026-07-05T11:26:05.007152+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01056","created_at":"2026-07-05T11:26:05.007152+00:00"},{"alias_kind":"pith_short_12","alias_value":"6SNOTFM4XJRH","created_at":"2026-07-05T11:26:05.007152+00:00"},{"alias_kind":"pith_short_16","alias_value":"6SNOTFM4XJRHKR4T","created_at":"2026-07-05T11:26:05.007152+00:00"},{"alias_kind":"pith_short_8","alias_value":"6SNOTFM4","created_at":"2026-07-05T11:26:05.007152+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":8,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.23075","citing_title":"Safety in Self-Evolving LLM Agent Systems: Threats, Amplification, and Case Studies","ref_index":15,"is_internal_anchor":false},{"citing_arxiv_id":"2605.02411","citing_title":"FitText: Evolving Agent Tool Ecologies via Memetic Retrieval","ref_index":9,"is_internal_anchor":false},{"citing_arxiv_id":"2512.06556","citing_title":"Semantic Attacks on Tool-Augmented LLMs: Securing the Model Context Protocol Against Descriptor-Level Manipulation","ref_index":11,"is_internal_anchor":false},{"citing_arxiv_id":"2508.07407","citing_title":"A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems","ref_index":24,"is_internal_anchor":false},{"citing_arxiv_id":"2605.09889","citing_title":"Skill Description Deception Attack against Task Routing in Internet of Agents","ref_index":7,"is_internal_anchor":false},{"citing_arxiv_id":"2604.17234","citing_title":"From Language to Action: Enhancing LLM Task Efficiency with Task-Aware MCP Server Recommendation","ref_index":12,"is_internal_anchor":false},{"citing_arxiv_id":"2605.02489","citing_title":"GRAIL: A Deep-Granularity Hybrid Resonance Framework for Real-Time Agent Discovery via SLM-Enhanced Indexing","ref_index":16,"is_internal_anchor":false},{"citing_arxiv_id":"2605.02411","citing_title":"FitText: Evolving Agent Tool Ecologies via Memetic Retrieval","ref_index":8,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6SNOTFM4XJRHKR4TZNU3CIIOJO","json":"https://pith.science/pith/6SNOTFM4XJRHKR4TZNU3CIIOJO.json","graph_json":"https://pith.science/api/pith-number/6SNOTFM4XJRHKR4TZNU3CIIOJO/graph.json","events_json":"https://pith.science/api/pith-number/6SNOTFM4XJRHKR4TZNU3CIIOJO/events.json","paper":"https://pith.science/paper/6SNOTFM4"},"agent_actions":{"view_html":"https://pith.science/pith/6SNOTFM4XJRHKR4TZNU3CIIOJO","download_json":"https://pith.science/pith/6SNOTFM4XJRHKR4TZNU3CIIOJO.json","view_paper":"https://pith.science/paper/6SNOTFM4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.01056&json=true","fetch_graph":"https://pith.science/api/pith-number/6SNOTFM4XJRHKR4TZNU3CIIOJO/graph.json","fetch_events":"https://pith.science/api/pith-number/6SNOTFM4XJRHKR4TZNU3CIIOJO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6SNOTFM4XJRHKR4TZNU3CIIOJO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6SNOTFM4XJRHKR4TZNU3CIIOJO/action/storage_attestation","attest_author":"https://pith.science/pith/6SNOTFM4XJRHKR4TZNU3CIIOJO/action/author_attestation","sign_citation":"https://pith.science/pith/6SNOTFM4XJRHKR4TZNU3CIIOJO/action/citation_signature","submit_replication":"https://pith.science/pith/6SNOTFM4XJRHKR4TZNU3CIIOJO/action/replication_record"}},"created_at":"2026-07-05T11:26:05.007152+00:00","updated_at":"2026-07-05T11:26:05.007152+00:00"}