{"id":"jordan-jarvis-jenkins-mcp-enterprise","name":"jenkins-mcp-enterprise","af_score":49.0,"security_score":55.5,"reliability_score":27.5,"what_it_does":"Provides a Python-based Model Context Protocol (MCP) server that connects to one or more Jenkins instances to diagnose build failures, explore sub-build hierarchies, trigger builds, discover job parameters, and extract/search log content. It supports configurable diagnostic rules and optionally semantic/vector search for cross-build similarity.","best_when":"You have complex Jenkins pipelines (including deep sub-build structures) and want an agent to investigate failures and extract actionable recommendations from large log outputs across multiple Jenkins instances.","avoid_when":"You need formal API contracts (OpenAPI) or strong, documented operational guarantees (SLA, retries, idempotency semantics) out of the box, or you cannot safely store/process Jenkins credentials and large build logs in your own environment.","last_evaluated":"2026-03-30T15:32:33.328042+00:00","has_mcp":true,"has_api":false,"auth_methods":["Jenkins per-instance token authentication (Jenkins API token)","Token-based access to the MCP server (mentioned, but exact mechanism not specified in provided text)"],"has_free_tier":false,"known_gotchas":["Requires providing full Jenkins URLs (including job path and build number) for correct instance routing.","Large log handling is emphasized, but there is no documented limit/error behavior for extremely large requests or timeouts.","Semantic/vector search is optional and may require additional dependencies and a local vector store (Qdrant) configuration."],"error_quality":0.0}