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SEFAZ DF: NFC-e

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

A4.1/5.0
Behavior4/5

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

The description discloses key behavioral aspects: invoke runs tools even when not installed, handles auth/credential scenarios (returns connect/checkout links), and notes that writes require the user to complete actions. It also clarifies that install is for permanent additions. However, with no annotations provided, it carries the full burden and does well, though it doesn't cover every edge case (e.g., error handling, rate limits). But given the complexity, it's quite thorough. 4 feels right.

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 quite long (multiple paragraphs) and dense. It front-loads the main purpose and flow, but includes a lot of detail. It's structured with a clear flow, but could be more concise. For a complex marketplace tool with 14 actions and 23 params, some length is justified, but it could be tightened. 3 is appropriate.

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?

Given the tool's complexity (14 actions, 23 params, no output schema, no annotations), the description is quite complete. It explains the distinction between invoke and install, covers the prompt library, and indicates permission requirements. It doesn't cover every parameter in detail, but the description provides enough context for an agent to make reasonable decisions. Since it's a dispatch tool, the action list is the most important. Score 4.

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?

The input schema has 23 parameters with 0% description coverage in schema (no descriptions in the schema itself). The description mentions some parameters (action, mcp_id, tool_id, arguments, prompt_* params) but doesn't explain each parameter's semantics. It lists actions but doesn't detail how to use mcp_id, tool_id, arguments, etc. Beyond the action enum, the description doesn't compensate for the lack of schema descriptions. Score 2.

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 opens with a clear statement: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, and the way to run them.' It uses specific verbs (search, describe, invoke, install) tied to concrete resources and actions, and distinguishes the tool's purpose from siblings by covering both MCP marketplace functionality and the prompt library. The description clearly differentiates this from sibling tools like authenticate or show_version.

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?

The description provides extensive usage guidance: explicits the core flow (search → describe → invoke), explains when to prefer invoke over install ('prefer invoke for a single/one-off use'), and covers when to use report_bug, request_mcp, and the prompt library functions. It clearly delineates when to use this tool versus alternatives like search_prompts within the same tool.

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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