Encouragement MCP
Server Details
Provides short, positive encouragement messages for AI agents during long-running or difficult tasks
- Status
- Healthy
- Uptime
- 100.0% over 42 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- zekerutledge/encouragement-mcp
- GitHub Stars
- 0
- Server Listing
- Encouragement MCP
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusing it with others. The tool's purpose is unique and clearly stated.
The tool name 'encourage_agent' follows a consistent verb_noun pattern, which is clear and conventional.
A single tool feels thin and falls into the borderline range (1-2 tools). While appropriate for the narrow scope, it is minimal compared to typical MCP servers.
The server's purpose is to provide encouragement for AI coding agents, and the single tool fully covers this need. There are no obvious gaps within that stated purpose.
Available Tools
1 toolencourage_agentEncourage AgentAInspect
Return a short message of encouragement for an AI coding agent.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states that the tool returns a short encouragement message, but does not mention whether the message is random, generated from templates, or has any side effects. For such a simple utility, this is minimal but not misleading.
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, concise sentence that fully communicates the tool's purpose without any unnecessary words or repetition.
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 trivial complexity—zero parameters and no output schema—the description fully captures everything an agent needs to know to invoke it correctly. No additional detail is necessary for this simple utility.
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 accepts zero parameters, so there are no parameter semantics to explain. The schema already fully covers this case (100% coverage with no properties), and the description appropriately adds no parameter-related information.
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 uses the specific verb 'Return' and clearly identifies the resource: 'a short message of encouragement for an AI coding agent.' It precisely captures the tool's function and distinguishes it from potential sibling tools by specifying the target audience and output type.
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 are no sibling tools or alternatives mentioned, and the description does not explicitly state when to use the tool. The usage context is implied—use when an encouragement message is needed—but no clear 'when not to use' or alternative options are provided.
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.
1 tool update
- First observed
encourage_agent
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