Accept the counterparty's current proposal. Only the side that did NOT make the last proposal can accept. Intent becomes matched, other bids are rejected.
| Name | Required | Description | Default |
|---|---|---|---|
| bid_id | Yes | Bid id (bid_...) | |
| 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 provided, the description carries the behavioral disclosure burden. It clearly states the important side effects: the intent becomes matched and other bids are rejected. It could additionally note irreversibility or failure behavior, but the core mutating consequences are disclosed.
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?
Two sentences carry all the essential information: the action, the precondition, and the postconditions. There is no filler, and the most important constraint is positioned immediately after the action.
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 two-parameter tool with no output schema, the description covers the precondition, the action, and the outcome. It does not describe return values or error cases, but those are less critical given the low complexity and the clear side effects.
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 has 100% parameter coverage, so the baseline is 3. The description adds meaningful semantic context by indicating that the bid_id should refer to the counterparty's current proposal, not just any bid. This helps the agent select the correct identifier.
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 clearly identifies the action ('Accept'), the target ('the counterparty's current proposal'), and the overall effect ('Intent becomes matched, other bids are rejected'). This distinguishes it well from sibling bid-related tools like reject_bid, withdraw_bid, and place_bid.
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?
It gives an explicit eligibility condition: only the side that did NOT make the last proposal can accept. This is strong usage guidance, though it does not explicitly name alternative tools or describe scenarios where reject_bid or withdraw_bid would be preferable.
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.