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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

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Despite annotations already carrying readOnly=false, openWorld=true, idempotent=false, destructive=false, the description adds substantial behavioral detail: invoke runs one-off without installing or bloating the tool list, credential gaps return a connect link, payment gaps return a checkout/top-up link, writes require workspace owner/admin, and the prompt share link opens without login. These behaviors are not visible in the annotations and are clearly disclosed.

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 but densely informative and thematically organized: core flow first, then invoke-specific caveats, billing/auth, write-permission context, and the separate prompt library. Every sentence adds value, but the sheer volume of detail makes it harder to parse quickly; better paragraph breaks would help.

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?

For a 14-action dispatcher with no output schema and 23 undocumented parameters, the description is unusually complete: it covers discovery, invocation, one-off vs permanent install, auth, payment, permissions, billing actions, and prompt-library behavior. Still, some actions are omitted (resume is never described, uninstall only appears in the permissions sentence) and it does not describe expected return shapes, which would be materially useful for a no-output-schema tool.

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 a heavy burden, and it does decode the action enum and core flow concepts like action, query, mcp_id, tool_id, and arguments. However, many parameters are left completely untouched: limit, immediate, tier_slug, request_name, cancel_reason, cancel_comment, report_context, prompt_body, prompt_slug, prompt_tool, prompt_vars, conversation, prompt_title, prompt_description, prompt_targets, prompt_category, and request_details. The agent must infer much of the parameter semantics from names and defaults alone.

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 states an exact purpose: it is the mcp.ai marketplace used to discover, describe, and run MCPs/tools. It explains the core action flow (search -> describe -> invoke) and explicitly names the intent categories it covers ('find an MCP that does X', 'consulta um CPF'). It also separates the prompt-library function from the MCP-catalog function, making the dual nature clear and avoiding confusion with sibling tools.

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 gives explicit when-to-use guidance: prefer invoke for single/occasional use, use install only to make an MCP PERMANENT, use list_tools to see callable tools now, subscribe/cancel for per-MCP billing, report_bug for feedback, and request_mcp when nothing fits. It even tells the agent what to do when a connect or checkout link is returned (user opens it, then retry). This is strong routing guidance.

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

B3.1/5.0
Disambiguation3/5

Most tools target distinct resource+action pairs, but the reporting/query side is crowded: get_balances, transactions_list_results, get_financial_summary, get_monthly_overview, and the category/tag reports overlap heavily. Long descriptions disambiguate bases and use cases, but an agent must read carefully to avoid picking the wrong report or list variant.

Naming Consistency4/5

Organizze tools overwhelmingly follow a consistent organizze_<verb>_<noun> snake_case pattern with create_, list_, get_, update_, and delete_ prefixes. Deviations like transactions_list_results, the mass_* versus update_transactions_* bulk variants, and unprefixed platform tools keep it from being perfect.

Tool Count1/5

68 tools is far beyond the practical agent surface and includes many near-variant list/report/mass tools plus six unrelated platform-level tools. Even though the finance domain is broad, this count creates an extreme mismatch for efficient tool selection.

Completeness3/5

The core finance lifecycle is well covered: accounts, cards, categories, budgets, transactions, invoices, transfers, and reports all have substantial CRUD or equivalent support. However, some referenced operations are missing entirely, such as delete_recurrence, clear_latest_imports, and remove_from_latest_imports, and transfers/recurrences lack full lifecycle coverage.