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Qase MCP Server

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by qase-tms

qase_project_context

Read-onlyIdempotent

Gather all project metadata in one request: project details, suites, milestones, environments, custom fields, and users. Start here to avoid multiple API calls.

Instructions

Get full project context in one call: project details, suites tree, milestones, environments, custom fields, and users. Cached for 5 minutes. Use this as the first call when starting work with a project — it seeds all the metadata the LLM needs without making 6 separate list calls. Each collection returns its first 100 entities by default; the coverage field reports { total, loaded, truncated } per collection, so check it before assuming a list is complete. Pass full: true to page through everything.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesProject code (2-10 uppercase letters, numbers, or underscores)
fullNoPage through every suite, milestone, environment, custom field, and user instead of fetching only the first 100 of each (default: false). Use this when a collection is reported as truncated and you need the complete set — it costs one API call per 100 entities and can return thousands of items, so prefer the targeted list tools or qql_search when you only need a subset.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
usersNoTeam members list
suitesYesSuites list with entities array
projectYesProject details
coverageYesPer-collection completeness: each of suites, milestones, environments, custom_fields, and users maps to { total, loaded, truncated }. When truncated is true the list holds only the first `loaded` of `total` entities — re-call with full: true for the rest.
milestonesYesMilestones list
environmentsYesEnvironments list
custom_fieldsNoCustom fields list
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses caching ('Cached for 5 minutes'), pagination defaults ('first 100 entities by default'), truncation reporting via 'coverage' field, and the cost/behavior of 'full: true' ('costs one API call per 100 entities'). These are valuable operational details not present in annotations.

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

Conciseness5/5

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

The description is five sentences, front-loaded with the tool's purpose and value, then usage guidance, then pagination behavior. No redundant or tangential information.

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

Completeness5/5

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

With annotations declaring read-only/idempotent and an output schema present, the description covers the necessary aspects: what the call returns at a high level, when to use it, caching, pagination limits, truncation handling, and full-page behavior. This fully equips the agent to decide when to call and how to interpret results.

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

Parameters3/5

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

The input schema already describes both parameters with high detail ('code' format, 'full' behavior), giving 100% coverage. The description reinforces the 'full' parameter's purpose and mentions checking the 'coverage' field, but adds little new parameter-level semantics beyond the schema.

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

Purpose5/5

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

The description clearly states the tool's function: 'Get full project context in one call' and enumerates the included data types (suites tree, milestones, environments, custom fields, users). It also distinguishes from sibling tools by positioning it as the initial call that avoids '6 separate list calls,' making the purpose specific and differentiated.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance: 'Use this as the first call when starting work with a project.' It also provides exclusions and alternatives: 'prefer the targeted list tools or qql_search when you only need a subset.' This clearly sets usage boundaries.

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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