jenkins-mcp-enterprise

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.

Evaluated Mar 30, 2026 (21d ago)
Repo ↗ Infrastructure mcp jenkins python ai-diagnostics ci-cd devops log-analysis semantic-search automation
⚙ Agent Friendliness
49
/ 100
Can an agent use this?
🔒 Security
56
/ 100
Is it safe for agents?
⚡ Reliability
28
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
75
Documentation
60
Error Messages
0
Auth Simplicity
65
Rate Limits
0

🔒 Security

TLS Enforcement
70
Auth Strength
65
Scope Granularity
35
Dep. Hygiene
55
Secret Handling
50

Uses Jenkins API tokens per configured instance and mentions SSL verification and Docker network isolation, but provided material does not confirm TLS-by-default for the MCP endpoint, how MCP access tokens are stored/rotated, whether secrets are masked in logs, or whether least-privilege/scoped permissions are implemented.

⚡ Reliability

Uptime/SLA
10
Version Stability
45
Breaking Changes
20
Error Recovery
35
AF Security Reliability

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.

Use Cases

  • AI-assisted diagnosis of failed Jenkins pipeline builds using log extraction and failure analysis
  • Navigating nested Jenkins sub-builds to find root causes
  • Triggering Jenkins builds (sync/async) and monitoring sub-build status
  • Finding similar failure patterns across prior build history using semantic/vector search
  • Configuring organization-specific diagnostic rules and recommendation templates

Not For

  • Direct human-facing CI dashboards or Jenkins replacements (it is an integration layer for AI tools)
  • Public internet exposure without an additional security perimeter and access controls
  • Environments requiring a fully managed SaaS offering (appears intended for self-hosting)

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
No
Webhooks
No

Authentication

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)
OAuth: No Scopes: No

README describes per-instance credentials in YAML (username + token) and an MCP-server token-based access, but does not provide detailed scope definitions or auth flows.

Pricing

Free tier: No
Requires CC: No

Project appears self-hosted; no hosted pricing information is present in provided material.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

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.

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Scores are editorial opinions as of 2026-03-30.

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Packages Evaluated
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Need Evaluation
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