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Glama
Zoya-Ammar

AI Agent Release Assurance MCP

by Zoya-Ammar

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
assess_release_readinessB

Calculate an explainable GO, CONDITIONAL_GO, or NO_GO recommendation.

get_failed_testsB

Return failed and blocked tests, optionally filtered by criticality.

find_defect_hotspotsB

Rank release components by the weighted risk of unresolved defects.

recommend_regression_testsC

Build a risk-based regression plan grounded in test and defect evidence.

Prompts

Interactive templates invoked by user choice

NameDescription
release_go_no_goGuide an evidence-based release readiness review.

Resources

Contextual data attached and managed by the client

NameDescription
releases_resourceList the synthetic releases available for analysis.

TDQS

B3.4/5.0

Scored across 4 tools

Disambiguation4/5

Each tool produces a distinct output: a GO/NO-GO decision, a filtered list of test failures, a component risk ranking, and a regression test plan. find_defect_hotspots and recommend_regression_tests share an evidence base of defect/test risk, but their purposes are clearly separated by output type, so misselection is unlikely.

Naming Consistency5/5

All four tools follow a consistent verb_noun snake_case pattern (assess_release_readiness, get_failed_tests, find_defect_hotspots, recommend_regression_tests). The verb clearly signals the action (assess, get, find, recommend) and the noun signals the resource, making the pattern highly predictable.

Tool Count5/5

Four tools is on the lean side but well-scoped for release assurance: each tool fills a distinct role covering evidence gathering, risk analysis, planning, and final decision. There is no redundancy or bloat, and every tool earns its place in the pipeline.

Completeness4/5

The set forms a coherent end-to-end release readiness workflow: pull test failures, rank defect hotspots, build a regression plan from that evidence, and produce a final GO/NO-GO assessment. Minor gaps exist, such as no tool to drill into individual defect details or fetch component/change scope, but agents can work around these.

Maintenance

ActivityMaintained
ResponsivenessNo issues