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mcp-server

by com.koongo

list_projects

Read-only

List your projects. Each item is {projectId, code, name, apiStatus, dataStatus, language, customerId, customerEmail}. Call this FIRST when you don't know which project to act on, or when another tool returns project_id_required. Let the user pick, then pass the chosen projectId to the other tools. When you own a single project you usually don't need this — the other tools infer it. Pass query to search projects by name, code, or owner email. IMPORTANT: if the call returns an EMPTY list, do not assume there are no projects — some accounts only return projects that MATCH a search term, so ask the user what to look for (a project name/code or the owner's email) and retry with a query. A broad search may be capped, so keep the query specific. apiStatus GRANTED = active; REVOKED/OVERLIMIT projects are listed too so the user sees them. After the user picks, the usual next step is get_import_status for that projectId.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoOptional search term to filter projects by name, code, or owner email.

TDQS

A5/5.0
Behavior5/5

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

Beyond the readOnly/destructive annotations, it discloses important hidden behavior: an empty list does not mean no projects, broad searches may be capped, and REVOKED/OVERLIMIT projects are still listed. It also explains apiStatus semantics, adding real operational context.

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 long but every sentence earns its place: core purpose and return shape up front, then usage guidance, edge cases, and next steps. There is no filler or redundant repetition of the schema.

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?

With no output schema, the description still provides the item structure, status meanings, empty-list caveat, and a suggested next step. An agent has enough context to invoke it correctly and handle unusual responses.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema covers 100% of the single `query` parameter, the description adds substantial value by naming what can be searched (name, code, owner email), warning that broad searches may be capped, and advising specific queries. This is more than a restatement of the schema.

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 states exactly what the tool does ('List your projects'), enumerates the item shape, and frames it as the first discovery step when a projectId is unknown. It clearly distinguishes this tool from the many other project-requiring siblings.

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?

It gives explicit when-to-use guidance ('Call this FIRST when you don't know which project to act on'), when not to use it ('When you own a single project you usually don't need this'), search behavior, empty-list retry instructions, and the recommended follow-up tool. This is unusually complete.

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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TDQS

A4.2/5.0
Disambiguation4/5

Tools are organized around distinct resources (ads, marketplaces, feeds, orders, rules, sources) with clear action verbs, and descriptions explicitly disambiguate near-pairs like get_feed_status vs ad_status or set_feed_filter vs set_feed_attribute_filter. A few similarly named status/action pairs (e.g. ad_status vs get_ad, run_ad_item_action vs run_ad_operation) require careful reading, but overall the purposes are separable.

Naming Consistency4/5

The overwhelming majority follow a consistent verb_noun snake_case pattern (list_*, get_*, create_*, set_*, run_*, test_*). Minor deviations like ad_status and marketplace_status (noun-based status tools) and koongo_knowledge break the pattern slightly, but the convention is clearly recognizable and predictable.

Tool Count1/5

At 105 tools, the surface is extreme and far beyond the 50+ threshold, even for a complex e-commerce integration domain. Much of the bloat comes from systematic triplication across ads, marketplaces, and feeds (e.g. three nearly identical map_*_attribute tools, three list_*_items, three get_*_report) that a generic resource parameter could have consolidated.

Completeness4/5

The toolset covers the full lifecycle of feeds, ads, marketplaces, order connections, rules, and imports, including create/read/update/delete, status monitoring, item-level actions, validation, repair, and restore. Minor gaps exist, such as no delete for standalone order connections and limited update capabilities for some entities, but these are workable and do not create dead ends for the core workflows.

Resources