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MPT PI: Certidão Negativa de Feitos

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

A4.2/5.0
Behavior5/5

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

Discloses key behavioral traits beyond annotations: invoke runs one-off without installing or bloating the toolkit, returns connect/checkout links when needed, install makes MCPs permanent, and prompt links open without login. Annotations are minimal and not contradicted; the description adds substantial 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.

Conciseness3/5

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

The description is information-dense and every sentence adds value, but it is delivered as a long, run-on paragraph with heavy parentheticals and semicolons. Restructuring into bullets or action groups would make the 14-action surface much easier to scan and apply.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core marketplace flow, permissions, billing/auth edge cases, and prompt library well. However, it omits return-value shapes for most actions and fails to document the majority of the 23-parameter surface, which is a significant gap for a multi-action router with no output schema.

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

Parameters2/5

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

With 23 parameters and 0% schema description coverage, the description carries the full burden, but it only implicitly explains action, mcp_id, tool_id, arguments, and prompt_vars. Most parameters (limit, immediate, tier_slug, cancel_reason, prompt_body, request_details, etc.) are left undocumented, so the agent cannot reliably construct non-core calls.

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 clearly defines this as the mcp.ai marketplace catalog and execution layer, with an explicit core flow (search → describe → invoke) and a separate prompt-library capability. It distinguishes itself from sibling tools by covering catalog discovery, one-off invocation, installation, and billing rather than auth/connect/version utilities.

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?

Provides strong when-to-use guidance: prefer invoke for single/occasional use, use install only for permanent toolkit inclusion, and use list_tools to see what is currently callable. It also states that writes require workspace owner/admin and explains the connect/checkout retry flow, giving the agent clear decision rules.

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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