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Pawangunjkar

Jenkins MCP Server

by Pawangunjkar

jenkins_build

Trigger a Jenkins build for any job, including parameterized builds by passing parameters as a JSON string to specify branch, deploy flags, and other inputs for the selected Jenkins session.

Instructions

Trigger a build for a Jenkins job.

For parameterized builds, pass parameters as JSON string.

Args: job_name: Full job name parameters: Build parameters as JSON string, e.g. '{"BRANCH": "main", "DEPLOY": "true"}' (empty for non-parameterized jobs) session_name: Jenkins session to use

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_nameYes
parametersNo
session_nameNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden of behavioral disclosure. It doesn't state whether a trigger is async (returns quickly and build runs later), whether it requires a valid session/connection, whether it fails for disabled jobs, or any error behavior. For a build-triggering action, knowing async vs sync behavior is critical, yet it's not disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core purpose first. The Args section is efficient. Minor redundancy: it restates parameter meanings that are already in the schema, but the JSON example earns its place given 0% schema coverage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is an output schema (though not shown), which reduces the need to describe return values. However, for a trigger tool with 3 parameters and no annotations, the description is adequate but missing key behavioral context: does the tool block until build completes, return a queue item ID, or fire-and-forget? The description is functional but not rich enough for a mutation operation with zero annotation support.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for all parameters. It does explain parameters with a real example (JSON format for parameters), the default empty string for non-parameterized jobs, and the session_name. This adds meaningful value beyond bare parameter names, though session_name could use more clarity on what a 'Jenkins session' means.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first line clearly states the tool triggers a Jenkins job build, which is a specific verb+resource. This distinguishes it from siblings like jenkins_get_build_info or jenkins_stop_build, though it doesn't explicitly call out any sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage (when you want to trigger a build), and notes parameterized vs non-parameterized handling. However, it doesn't explicitly state when NOT to use it or contrast with siblings like jenkins_replay_pipeline or jenkins_get_build_info. Usage context is implied but not reinforced with exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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