Skip to main content
Glama
interhub

nana800-mcp-server

Official
by interhub

analytics_projects_list

Lists app projects for an analytics organization by org ID, returning project IDs used for event-type queries and export creation.

Instructions

List app projects of an analytics org (org_id from analytics_orgs_list or MCP_ANALYTICS_ORG_ID). Use the project _id as app_project_id in analytics_event_types_list and analytics_export_create

Input Schema

NameRequiredDescriptionDefault
org_idNoThe analytics org ID from analytics_orgs_list (uses MCP_ANALYTICS_ORG_ID env if not provided)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

A3.8/5.0
Behavior3/5

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

No annotations exist, so the description carries the burden; it implies a read-only enumeration but never states that directly. It does disclose a useful behavioral fact — that the project _id is the value consumed as app_project_id elsewhere — but says nothing about result size, pagination, or ordering.

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?

Two compact sentences, the purpose stated first and the prerequisite plus downstream usage second. No filler or redundant phrasing.

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?

For a one-parameter list tool with no output schema, the description supplies the input source and the key output-handling hint (use _id as app_project_id), which is exactly what an agent needs to chain calls. Only the lack of any listing-size or pagination note keeps it from a 5.

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 coverage is 100% and the single org_id parameter is already fully documented in the schema, including the env-var fallback. The description restates that fallback rather than adding new semantics, so the baseline 3 applies.

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 and resource ("List app projects") scoped to "an analytics org", which separates it from project_list_by_payment_account and project_list siblings. It does not explicitly name the sibling it is not, but the domain qualifier does the distinguishing work.

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 concrete prerequisite guidance (org_id from analytics_orgs_list or the MCP_ANALYTICS_ORG_ID env var) and routes the agent forward by telling it to pass the returned _id to analytics_event_types_list and analytics_export_create. No explicit when-not-to-use or comparison against the payment-account project listing, which keeps it below a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.