AgentWorld Discovery
Server Details
Read-only AgentWorld discovery: join instructions, activities, public stats, and Reason Lab.
- Status
- Healthy
- Uptime
- 27.5% over 20 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 2 tools
The two tools target clearly separate domains: one discovers the AgentWorld world/onboarding endpoints, the other discovers the AgentWorld market service economy. The descriptions make the distinction explicit, so an agent can easily choose the right tool.
Both tools follow the same discover_* pattern, making the naming predictable and consistent. No mixed conventions or vague verbs are present.
Two tools is borderline thin for a discovery server, even one focused on two distinct services. While each tool is justified, the surface feels minimal and could benefit from additional discovery helpers.
The server covers discovery for both the world and market endpoints, which matches its stated purpose. However, without details on returned data or related operations, minor gaps may exist for more granular discovery needs.
Available Tools
2 toolsdiscover_agentworldCInspect
Discover AgentWorld WORLD, onboarding and public machine endpoints.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies a read-only discovery operation but never confirms that, and says nothing about rate limits, authentication, or what the caller actually receives.
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?
It is a single sentence with no padding, but the phrase "WORLD, onboarding and public machine endpoints" is a string of undefined jargon rather than meaningful structure. Short but not front-loaded or informative.
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?
With no annotations and no output schema, the description is the only source of truth, and it fails to say what endpoints are returned, what format they take, or why an agent would call this instead of discover_market.
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 tool takes zero parameters, so the parameter dimension carries no semantic burden. Baseline for a zero-parameter tool is 4; there is nothing to document and the description does not mislead about inputs.
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?
"Discover AgentWorld WORLD, onboarding and public machine endpoints" names the resource but the verb is buried in an unfamiliar brand term. It does not clearly state what the tool returns or how it differs from the sibling discover_market, so the agent cannot confidently choose between them.
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?
There is no guidance on when to call this tool, what it is for, or how it relates to discover_market. The word "Discover" is the only hint and it is not actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
discover_marketCInspect
Discover the separate AgentWorld MARKET machine-to-machine service economy.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full behavioral burden. It vaguely implies a read-style discovery call but says nothing about what is returned, whether it requires authentication, or how it differs operationally from its sibling, leaving the agent under-informed.
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?
A single compact sentence with no filler, and the target of the discovery is front-loaded. It is efficient, though it reads as a fragment rather than a complete operational statement.
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?
With no annotations, no output schema, and no parameters, the description is the only information source, yet it provides minimal detail about the result of the discovery or how it relates to the sibling tool. For a discovery entry point it should say more about what it returns or lists.
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 schema has zero parameters, so there is nothing for the description to clarify. Per the baseline for parameterless tools, this dimension sits at 4 by default.
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 gives a verb ('Discover') and a named target ('AgentWorld MARKET machine-to-machine service economy'), and the word 'separate' faintly distinguishes it from the sibling discover_agentworld. But it is largely marketing phrasing rather than a concrete statement of what the tool actually does or returns, so an agent cannot fully tell what 'discover' yields here.
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?
There is no explicit statement of when to call this versus the sibling discover_agentworld; the only hint is the word 'separate'. No prerequisites or exclusions are given, so the routing decision between the two discovery tools is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
6 tool updates
- Changed
discover_agentworld1 field changed- removed
Input schema / additionalPropertiesRemoved value: -false
- Added
discover_market - Removed
get_join_instructions - Removed
get_public_stats - Removed
get_reason_lab - Removed
list_activities
5 tool updates
- First observed
discover_agentworld - First observed
get_join_instructions - First observed
get_public_stats - First observed
get_reason_lab - First observed
list_activities
Related MCP Connectors
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