Qase MCP Server

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by qase-tms

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TypeScript

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Project context

qase_project_context

Read-onlyIdempotent

Get full project context in one call: details, suite tree, milestones, environments, custom fields, and users. Start here to replace six list calls when working with a project.

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

Name	Required	Description	Default
`code`	Yes	Project code (2-10 uppercase letters, numbers, or underscores)
`full`	No	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.

Output Schema

TableJSON Schema

Name	Required	Description
`users`	No	Team members list
`suites`	Yes	Suites list with entities array
`project`	Yes	Project details
`coverage`	Yes	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.
`milestones`	Yes	Milestones list
`environments`	Yes	Environments list
`custom_fields`	No	Custom fields list

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv2.1.1Aug 14, 2026

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"
+]

Addedv2.0.0Jul 29, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Despite annotations already covering the read-only/idempotent safety profile, the description adds substantial behavioral context: cost (six API calls behind one call), cold latency (0.5-1.3s), response size (16-48KB), a 5-minute cache with ~5ms repeat calls, and the truncation/coverage semantics per collection. The warning to check the coverage field before assuming completeness is exactly the kind of behavior an agent needs to know.

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?

Every sentence earns its place, and the structure is optimally front-loaded: purpose first, then when to call, the truncation caveat, alternatives, then cost/caching details. The length looks long, but for a tool that aggregates six calls and has real cost and truncation implications, the density is justified and there is zero filler.

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 complex seeding tool, the description covers everything an agent needs: what is returned, truncation behavior and how to detect it, how to get the full set, cost and latency, caching, and routing to alternatives. The presence of an output schema means return shapes need no description, and the annotations carry the safety profile, so this is complete rather than padded.

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 coverage is 100%, so the baseline is 3. The description adds meaningful semantics to the `full` parameter beyond the schema: when to use it (collection reported as truncated), its cost model (one extra call per 100 entities), and its risk (can return thousands of items, prefer targeted tools). The `code` parameter gets no additional description-level semantics, but the schema already fully covers it. One step above 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 opens with a specific verb-plus-resource statement ('Seed everything about a project in one call') and enumerates the exact contents (project details, suite tree, milestones, environments, custom fields, users). It actively distinguishes itself from siblings by noting it replaces six list calls and by naming qase_get and qql_search as cheaper or better-suited alternatives for other scenarios.

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?

Explicit when-to-use guidance is front and center: 'This is the first call to make when starting work on a project.' It also names concrete when-not-to-use cases with alternatives ('For a single record you already have the ID for, qase_get is cheaper; for filtered or cross-project questions, use qql_search') and reiterates the preference for targeted tools in the full parameter's schema description. Nothing is left to inference.

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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