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Glama

SEFAZ PE: Dívida Ativa

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?

With annotations that are all near-default values (readOnly=false, destructive=false), the description carries the full transparency burden and delivers: it discloses that writes require workspace owner/admin, that invoke runs tools 'pontualmente' without permanent installation, and that credential/payment gaps return connect or checkout links requiring user action before retry. No contradiction exists — the write-permission statements are consistent with readOnlyHint=false.

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?

The description is a single unbroken paragraph — a dense wall of text with no section breaks or bullet points. While nearly every sentence carries some information, the lack of structure makes the middle sections (billing, install vs invoke, prompt library) blur together and burdens the agent's parsing. It front-loads purpose well but is neither concise nor well-organized.

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?

For a tool this complex (23 params, 14 actions, billing, installs, prompt library) with no output schema and minimal annotations, the description covers the core discovery and run flows thoroughly, including auth requirements and retry behavior. But it leaves gaps: no return-value descriptions, no cancel/resume flow details, and unexplained immediate/tier_slug semantics. It is adequate for the main paths but not complete for a tool of this magnitude.

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?

With 0% schema coverage and 23 parameters, the description faces a heavy burden and compensates only partially. It explains the action enum values, the tool_id selection flow, arguments for invoke, prompt_vars variable filling, and prompt_slug sharing links. However, many parameters remain entirely unexplained — cancel_reason, cancel_comment, immediate, tier_slug, conversation, request_name, request_details, prompt_body, prompt_targets, report_context — leaving real gaps.

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 opening sentence identifies this as 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them', which is a specific and accurate purpose. It clearly explains the search→describe→invoke core flow and differentiates this catalog tool from siblings like connect and authenticate. However, the scope is sprawling (14 actions spanning billing, installs, and a prompt library), making the tool's verb diffuse despite the strong opening.

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?

The description provides strong internal usage direction: the explicit core flow (search→describe→invoke), the clear 'prefer invoke for one-off, use install only for permanent' heuristic, and the retry-after-connect/checkout-link logic. It also positions list_tools for what is callable right now and distinguishes the prompt library actions. It lacks explicit when-not-to-use versus sibling tools, but the internal action guidance is genuinely helpful.

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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