{"id":"W7143321693","doi":"10.1109/emergin67762.2025.11450575","title":"A Comprehensive Study and Implementation of Agentic AI via MCP Servers","year":2025,"lang":"","type":"article","venue":"","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Server; Focus (optics); Key (lock); Troubleshooting; The Internet","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003840431,0.0005644226,0.0005308046,0.001312327,0.00126196,0.005950389,0.002819711,0.001413557,0.004949202],"category_scores_gemma":[0.01006788,0.0007986797,0.0005020631,0.00402886,0.001148247,0.009915809,0.002341593,0.002360294,0.003265863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003137482,"about_ca_system_score_gemma":0.005594552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003616685,"about_ca_topic_score_gemma":0.001879954,"domain_scores_codex":[0.9961976,0.00106909,0.0002760178,0.0004164067,0.001690408,0.0003505635],"domain_scores_gemma":[0.9933972,0.001845795,0.0004432737,0.001753699,0.002154858,0.000405152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001845607,0.0003083003,0.004321052,0.001841416,0.0000802357,0.0006016708,0.002832736,0.0166526,0.01869221,0.4081203,0.02071251,0.5256525],"study_design_scores_gemma":[0.00003786228,0.0003978304,0.004286169,0.001229184,0.000129534,0.0009614321,0.00161508,0.08597735,0.03456066,0.03969137,0.8309991,0.0001144731],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.121333,0.02977797,0.6542087,0.006180127,0.0007522333,0.0008979404,0.0007312865,0.008047424,0.1780714],"genre_scores_gemma":[0.6265571,0.02335389,0.308996,0.001366638,0.0003597155,0.0006221208,0.001783451,0.001527548,0.03543365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005950389,"threshold_uncertainty_score":0.02276415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01396062425421813,"score_gpt":0.3091242298654012,"score_spread":0.295163605611183,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}