Zain Ahmed Platform MCP Server

get_projects

Read-only

Use this tool when listing or filtering verified enterprise production case studies by domain category or technology stack. Returns a paginated list of system blueprints, tech stacks, and business metrics.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_projects"
  }
}

Input Schema

Name	Required	Description
`tech`	No	Filter by technology used (e.g. Kubernetes, Terraform, ArgoCD, GCP, AWS)
`limit`	No	Max number of projects to return (default: 10)
`offset`	No	Offset for pagination (default: 0)
`category`	No	Category filter (e.g. FinTech, Consulting, Healthcare, Cloud Engineering)

Output Schema

Name	Required	Description	Default
`total`	Yes
`projects`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered structurally. The description adds that results are paginated and that items contain blueprints, tech stacks and business metrics, but return content is largely redundant given an output schema exists, and it says nothing about how the filters combine or default behavior.

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?

Two sentences, front-loaded with the triggering condition ("Use this tool when..."), then the return shape. Efficient, with only mild redundancy in the return-content sentence.

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?

With annotations covering safety, a full input schema and an output schema, the description supplies the missing piece – the listing/filtering intent and pagination nature. Only the interaction between filters and pagination defaults is left unstated, a minor gap for a simple read tool.

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?

Schema description coverage is 100%, with examples for tech and category, so the schema already carries the parameter meaning. The description only echoes the filter concepts (category, technology stack) without adding syntax, matching, or combination semantics, making the baseline 3 appropriate.

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?

States a specific verb (listing/filtering) and resource (verified enterprise production case studies) plus the two filter axes. It implicitly distinguishes the collection endpoint from the singular get_project_by_slug sibling, though it never names that sibling explicitly.

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

Usage Guidelines4/5

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

Gives clear context for when to use it: listing or filtering by domain category or technology stack. It stops short of exclusions, e.g. directing the agent to get_project_by_slug for a single project, so it does not reach the when/when-not bar of a 5.

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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