uselessfacts
Server Details
Uselessfacts MCP — wraps uselessfacts.jsph.pl API (free, no auth)
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-uselessfacts
- GitHub Stars
- 0
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Tool Definition Quality
Average 3.3/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one fetches a random fact, while the other retrieves today's specific fact of the day. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the need for randomness versus timeliness.
Both tool names follow a consistent adjective_noun pattern (random_fact, today_fact), using snake_case and clear descriptors that align with their functions. This predictability enhances usability and reduces confusion.
With only two tools, the server feels thin for a fact-fetching service, as it lacks operations like searching facts by category, listing historical facts, or managing user preferences. While the tools cover basic retrieval, the scope is minimal and could benefit from additional functionality to support more complex agent interactions.
The server provides core retrieval operations (random and daily facts), but there are notable gaps such as the inability to search, filter, or access facts beyond these two methods. For a fact service, this limits agents to only basic queries without support for more nuanced or historical data access.
Available Tools
2 toolsrandom_factBInspect
Get a random useless (but interesting) fact.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the fact is 'useless (but interesting)', which adds some context about content quality, but doesn't describe response format, potential errors, rate limits, or other behavioral traits. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
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 perfectly concise at 7 words, front-loading the core action ('Get a random...') with no wasted words. Every element ('useless (but interesting)') adds meaningful qualification without redundancy.
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?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It covers the basic purpose and distinguishes from the sibling, but lacks details about return format, error conditions, or other behavioral aspects that would be helpful for an agent invoking this tool.
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 has 0 parameters with 100% schema description coverage, so the schema already fully documents the absence of parameters. The description appropriately doesn't add parameter information beyond what the schema provides, maintaining focus on the tool's purpose rather than unnecessary parameter details.
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 states the tool's purpose with a specific verb ('Get') and resource ('random useless (but interesting) fact'). It distinguishes the tool from its sibling 'today_fact' by emphasizing randomness rather than date-specific facts. However, it doesn't explicitly contrast with the sibling beyond the 'random' vs 'today' distinction.
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 when to use this tool (when you want a random fact) versus its sibling (when you want today's fact), but this is only through contextual inference rather than explicit guidance. No explicit 'when-not-to-use' or alternative scenarios are provided beyond the basic contrast.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
today_factBInspect
Get today's useless fact of the day.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'useless fact', which hints at the content type, but doesn't describe response format, error handling, rate limits, or any other behavioral traits. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundant information. It's appropriately sized and front-loaded, making it easy for an agent to parse and understand immediately.
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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the return value looks like (e.g., format, structure), error conditions, or how it differs from 'random_fact'. For a tool with no structured metadata, the description should provide more context to ensure proper usage.
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 has 0 parameters, and the schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline expectation for a parameterless tool without introducing confusion or unnecessary details.
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 states the tool's purpose with a specific verb ('Get') and resource ('today's useless fact of the day'), making it immediately understandable. However, it doesn't explicitly differentiate from its sibling 'random_fact', which might offer similar functionality but with different temporal constraints or randomness.
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 provides no guidance on when to use this tool versus its sibling 'random_fact'. It lacks any context about alternatives, prerequisites, or specific scenarios where this tool is preferred, leaving the agent to infer usage based on the name alone.
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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