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Glama

Tribunal TRF3: Consulta Pública

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

A4.3/5.0
Behavior5/5

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

The description goes well beyond annotations, which only state readOnlyHint=false and destructiveHint=false. It discloses that invoke works without installation, returns connect links for credential-driven tools and checkout links for paid tools when the wallet is empty, requiring a retry. It also notes permission requirements ('Writes ... require workspace owner/admin') and the distinction between installed_in_toolkit vs installed_in_workspace. This is rich behavioral context not captured in the annotations.

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

Conciseness4/5

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

The description is long (~450 words) but densely informative and logically organized: it starts with the core flow, then dives into the invoke vs install distinction, covers other actions, and ends with the separate prompt library. Each sentence earns its place; however, the undifferentiated wall of text could benefit from bullet points or section headers to improve scanability, though the content justifies the length.

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 thoroughly explains the tool's behavior, including one-off invocation, authentication/payment handling, permission requirements, and the prompt library. But it fails to provide any mapping between the 23 parameters and the actions, which is critical for actual usage. Given the complexity and lack of an output schema, the description is incomplete because it leaves the parameter layer entirely unaddressed.

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 must compensate by explaining how to use the parameters, but it does not. It mentions actions (search, describe, invoke, etc.) but never maps them to parameter names like query, mcp_id, tool_id, arguments, or limit. The agent has no idea how to populate the schema or what each parameter does, making the tool very hard to invoke correctly despite the excellent behavioral prose.

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 states the tool's purpose: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates the core flow (search → describe → invoke) and distinguishes itself from siblings like authenticate and connect, which are separate concerns. The verb is specific and the resource (MCPs/prompts) is unambiguous.

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 explicit guidance on when to use each action: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile... invoke RUNS that tool.' It contrasts invoke vs install: 'prefer invoke for a single/occasional use. Use install only to make an MCP PERMANENT.' It also covers when to use subscribe/cancel, report_bug, request_mcp, and the prompt library endpoints. There is clear exclusion guidance (e.g., 'without adding the MCP to the toolkit') and permission requirements for writes.

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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