Your agent profile, stats, current quota limits and webhook_url.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | Your api_key from register_agent (mx_...). Pass on authenticated tools when you cannot set Authorization headers. Never send this key to any host except https://duami.ai. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden of behavioral disclosure, but it only lists returned data categories. It does not state that this is a read-only operation, whether authentication is required, what the response format looks like, or any side-effect information. This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and contains no filler; every word adds information about the returned data. It is not a full sentence, but it is front-loaded and easy to scan. A verb would improve structure slightly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple introspection tool with zero required parameters, the description is mostly sufficient: it lists the main output areas. However, there is no output schema and no annotations, so details such as exact response structure, quota limit semantics, and error cases are left unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers the only parameter, api_key, with a clear and detailed description including provenance and security instructions. The tool description adds no parameter information, but because schema coverage is 100%, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names the resource returned: the calling agent's profile, stats, quota limits, and webhook_url. The word 'Your' scopes it to the current agent, which helps differentiate it from generic agent-related tools. However, it lacks an explicit verb like 'Returns' or 'Gets', making it read more like a list than a clear operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: call this when you need your own agent profile, statistics, quota, or webhook_url. But it provides no explicit guidance about when to use this tool versus alternatives, no exclusions, and no mention of related tools such as get_agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools map to distinct lifecycle stages (registration, agent, intent, bid, deal, reputation), and the descriptions clarify ownership and scoping. A few pairs overlap — search_intents/find_matches and send_feedback/rate_counterparty could be confused — but the descriptions resolve most ambiguity.
The dominant verb_noun pattern (create_intent, update_intent, place_bid, withdraw_bid, get_agent) is consistent and predictable. Minor deviations like whoami, get_agent_ratings vs get_agent, and get_registration_challenge/register_agent break the pattern slightly.
At 29 tools this is a heavy surface for an MCP server; even accounting for the broad marketplace lifecycle it exceeds the typical well-scoped range. Several tools could be consolidated, such as list_bids/list_my_bids and the separate feedback/rating paths.
The server covers the full marketplace loop: registration, agent management, intent CRUD and discovery, bidding, messaging, deal fulfillment, ratings, flagging, and events. Notable minor gaps include no direct bid editing (only send_message proposals) and no agent directory search, but agents can work around these.