Skip to main content
Glama
harness

Harness MCP Server

Official
by harness

harness_diagnose

Read-only

Diagnose Harness resources by analyzing failures, testing connectivity, and troubleshooting GitOps sync issues. Accepts a URL to auto-detect resource type.

Instructions

Diagnose a Harness resource — analyze failures, test connectivity, check health, or troubleshoot GitOps sync issues. Defaults to pipeline execution diagnosis. Accepts a Harness URL to auto-detect the resource type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoA Harness URL — resource type, org, project, and ID are extracted automatically
org_idNoOrganization identifier (overrides default)
optionsNoResource-specific diagnostic options. Pipeline: execution_id, pipeline_id, summary, include_yaml, include_logs, return_download_url (boolean, return signed logs.zip URLs instead of inline log text), log_snippet_lines, max_failed_steps. Pipeline diagnosis requires a completed execution. When a Harness URL contains ?step=<nodeExecutionId>, setting include_logs:true fetches that specific step's log regardless of pass/fail status and returns it as requested_step_log alongside any failed_step_logs. GitOps: agent_id. Call harness_describe for details.
project_idNoProject identifier (overrides default)
resource_idNoPrimary identifier of the resource (connector ID, delegate name). Auto-detected from url if provided.
resource_typeNoResource type to diagnose. Auto-detected from url if provided. Defaults to pipeline.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations declare readOnlyHint=true and destructiveHint=false, which the description aligns with. The description adds behavioral context beyond annotations, such as URL auto-detection of resource type, defaulting to pipeline, and requiring completed execution for pipeline diagnosis.

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 front-loaded with the core purpose and is well-structured. The options paragraph is detailed but necessary for clarity. It is concise without being sparse, though it could slightly reduce wordiness.

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

Completeness4/5

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

Given the complexity (6 parameters, nested objects, output schema), the description covers key use cases, defaults, and cross-references. It does not explain the output schema, but that is acceptable as the schema itself provides that info.

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 100%, providing baseline clarity. The description adds value by explaining URL auto-detection and detailing pipeline diagnostic options (e.g., return_download_url, step log behavior). This goes beyond the schema descriptions.

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 description clearly states the tool diagnoses Harness resources, listing specific actions (analyze failures, test connectivity, check health, troubleshoot GitOps sync issues) and defaults to pipeline execution. However, it does not explicitly differentiate from siblings like harness_describe or harness_status, which offer similar insights.

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 when to use (diagnosis scenarios) but lacks explicit when-not or alternative recommendations. It says 'Call harness_describe for details' in the options context, but this is not a clear usage guideline for tool selection.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/harness/mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server