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qase-tms

Qase MCP Server

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by qase-tms

qase_project_context

Read-onlyIdempotent

Get all project context in one call—details, suites, milestones, environments, custom fields, users. Use as the first step to bootstrap queries; inspect coverage and set full to retrieve complete collections.

Instructions

Seed everything about a project in one call: project details, the full suite tree, milestones, environments, custom fields, and users. This is the first call to make when starting work on a project — it replaces six separate list calls and gives the model the metadata it needs to build any later query. Each collection returns its first 100 entities; the coverage field reports { total, loaded, truncated } per collection, so check it before assuming a list is complete, and pass full: true to page through everything. For a single record you already have the ID for, qase_get is cheaper; for filtered or cross-project questions, use qql_search. Cost: six API calls behind one tool call, 0.5-1.3s cold, and 16-48KB of response depending on project size. Cached for 5 minutes, so repeat calls inside that window return in about 5ms. full: true costs one extra call per 100 entities and can return thousands of items.

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

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changedv2.1.1
    • addedInput schema / properties / full
      Added value: +{
      +  "description": "Page 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.",
      +  "type": "boolean"
      +}
    • addedOutput schema / properties / coverage
      Added value: +{
      +  "description": "Per-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.",
      +  "type": "object"
      +}
    • changedOutput schema / required
      Previous value: -[
      -  "project",
      -  "suites",
      -  "milestones",
      -  "environments"
      -]New value: +[
      +  "project",
      +  "suites",
      +  "milestones",
      +  "environments",
      +  "coverage"
      +]
  2. Addedv2.0.0

TDQS

A4.9/5.0
Behavior5/5

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

The description adds substantial behavioral context beyond the annotations: 100-entity pagination limits per collection, the coverage field shape, truncation semantics, full:true behavior, cold vs. cached latency, response size, and cost in API calls. It also confirms read-only/idempotent behavior through 'Cached for 5 minutes' and 'repeat calls... return in about 5ms.'

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 dense but every sentence earns its place: purpose, first-call guidance, pagination behavior, alternatives, cost, latency, caching, and full-mode tradeoffs are all relevant for correct tool selection and invocation. The core purpose is front-loaded before performance and alternative details.

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?

For a tool with this complexity, the description covers what the tool returns, pagination limits, truncation detection, when to pass full:true, cost implications, alternatives, and caching behavior. The output schema handles the detailed return structure, so nothing essential is missing from the description.

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%, so both parameters are already documented. The description adds extra meaning for the full parameter by explaining the cost model ('one extra call per 100 entities') and directing users toward targeted tools when only a subset is needed. That goes beyond the schema baseline.

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 gives a specific verb and resource with an explicit inventory: 'Seed everything about a project in one call: project details, the full suite tree, milestones, environments, custom fields, and users.' It also clearly distinguishes itself from siblings by naming qase_get and qql_search as alternatives for different query patterns.

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?

Usage context is explicit: 'This is the first call to make when starting work on a project' and it 'replaces six separate list calls.' It also states when not to use it: 'For a single record you already have the ID for, qase_get is cheaper; for filtered or cross-project questions, use qql_search.' This gives the agent clear decision rules.

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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