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marketplace

The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. Covers capability requests like "find an MCP that does X", "consulta um CPF", "is there a tool for Y". Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs: search_prompts finds one, get_prompt returns its full text with {{variables}} filled, and publish_prompt saves a prompt and returns a shareable mcp.ai/p/ link that opens without login.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
actionNosearch
mcp_idNo
messageNo
tool_idNo
argumentsNo{}
immediateNo
tier_slugNo
prompt_bodyNo
prompt_slugNo
prompt_toolNo
prompt_varsNo{}
conversationNo[]
prompt_titleNo
request_nameNo
cancel_reasonNo
cancel_commentNo
prompt_targetsNo
report_contextNo
prompt_categoryNo
request_detailsNo
prompt_descriptionNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations are sparse (readOnlyHint: false, destructiveHint: false), so the description carries the burden — and it delivers. It discloses critical runtime behaviors: invoke runs one-off without installing ('runs the tool pontualmente'), returns connect links for auth, checkout links for empty wallets, openWorldHint=true aligns with the arbitrary capability requests stated. No contradiction with annotations, and substantial value is added beyond what the annotations state.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A ~300-word single unbroken paragraph with no bullets, line breaks, or examples. Mixed-language usage ('consulta um CPF', 'pontualmente') creates ambiguity. Dense semantically, but the structural choices force multiple re-reads to extract the flow. The information deserves 4s, but the presentation badly needs formatting.

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 exceptional complexity (23 params, no required fields, 14-action dispatcher, 3 sub-flows), the description covers capability discovery, one-off invocation, permanence semantics, billing/auth edge cases, permission requirements, and prompt library features. Very few gaps exist in content — mostly gaps in navigation/structure.

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 0% with 23 parameters and only 2 enums, putting a heavy burden on the description. The description does excellent work explaining the 'action' enum values (search→describe→invoke flow, search_prompts/get_prompt/publish_prompt), which is the semantic core. However, 16+ parameters (conversation, cancel_reason, prompt_targets, request_details, arguments, etc.) receive zero explanation, and the mcp_id/tool_id relationship is only implied, not stated.

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?

The opener 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them' clearly establishes identity and scope. It defines coverage boundaries ('Covers capability requests like...') which aids sibling differentiation, though the purpose is inherently diffuse across 14 actions and 3 sub-flows, and no single verb captures it.

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?

Provides explicit when-to-use logic: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' Also covers edge cases (auth connect links, payment top-up then retry) and permission requirements ('Writes... require workspace owner/admin'). Loses a point by not explicitly naming alternative tools or a decision tree for sibling differentiation.

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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