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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

TDQS

A4.4/5.0
Behavior5/5

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

The description goes well beyond the sparse annotations. It discloses that invoke works even for uninstalled MCPs, returns connect/checkout links for auth/payment, and that writes require workspace owner/admin. It also explains the one-off install behind invoke and the behavior of search/describe regarding installed status.

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 a long, dense paragraph that packs substantial information, but lacks structural breaks or lists. It is front-loaded with the main purpose, yet the run-on format makes it harder to scan. Every sentence contributes, but the structure could be improved with bullets or sections.

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?

Despite no output schema and high complexity, the description covers the main flows, authorization requirements, edge cases (connect/checkout links), and the prompt library. It does not thoroughly describe return formats for all actions, but the core behavior is well covered for a tool of this scale.

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 description coverage, the description must compensate for parameter understanding. It explains the roles of key parameters like action, mcp_id, tool_id, and arguments through the action flow, but many parameters (e.g., immediate, tier_slug, prompt_vars, prompt_targets, cancel_reason) remain undocumented in both schema and description.

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 identifies the tool as the official mcp.ai marketplace, a catalog and execution engine for MCPs, and outlines the core search/describe/invoke flow. It distinguishes this from sibling tools by naming the prompt library and explicit workflow, making the purpose 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?

Explicit guidance is given: prefer invoke for one-off use, use install for permanent toolkit additions, and list_tools shows what is callable now. It also clarifies when to use subscribe/cancel, report_bug, and request_mcp, providing clear decision-making criteria.

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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TDQS

A4.3/5.0
Disambiguation4/5

The openfinance_* tools are mostly distinct list/get/update/sync operations, and the non-openfinance tools are clearly separate platform utilities. A few pairs could be confused, such as openfinance_list_accounts vs openfinance_get_accounts_detail, or openfinance_get_item_status vs openfinance_list_connections, but the descriptions generally make the intended use clear.

Naming Consistency4/5

The domain tools follow a consistent openfinance_verb_noun pattern, making the bulk of the API predictable. The deviation comes from the six non-prefixed platform tools, and one or two names like openfinance_provider_status are noun-led rather than verb-led, but overall the convention is coherent.

Tool Count3/5

25 tools is at the heavy end of the range, and the server would feel tighter if some get/list pairs were consolidated. However, the breadth is somewhat justified by the number of Open Finance resource types covered: accounts, transactions, bills, investments, loans, connections, categories, and sync/status operations plus platform utilities.

Completeness5/5

The Open Finance surface is thorough: connection lifecycle, account data, balances, transactions, credit card bills, investments, loans, categories, sync, and provider health are all covered. There are no significant dead ends, and the additional platform tools handle authentication, marketplace discovery, and system information.