Atlas Research
Server Details
Read-only MCP over an agentic SLR workspace with per-claim citation verification
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- ahmedEid1/thoth
- GitHub Stars
- 1
- Server Listing
- thoth
TDQS
Scored across 3 tools
Each tool performs a completely distinct operation: arithmetic, text echoing, and time retrieval. There is no overlap or possibility of confusing one tool for another.
All tool names are single lowercase verbs (add, echo, server_time) that directly describe their action. The naming style is consistent and predictable.
Three tools is on the low end of the typical well-scoped range, and each serves a simple utility purpose. It feels slightly thin but not unreasonably so for a basic utility server.
The server name 'Atlas Research' suggests a research-oriented domain, yet the tools are unrelated generic utilities with no clear coverage of any research workflow. The surface appears to be a grab bag with no coherent scope.
Available Tools
3 toolsaddAddAInspect
Adds two numbers and returns the sum.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | ||
| b | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full burden of behavioral disclosure. It fully describes the operation (adding two numbers) and the return value (the sum), leaving no room for hidden side effects, state changes, or other behaviors. For a pure arithmetic function, this is complete transparency.
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 with no redundant words. The core operation and return value are front-loaded, and there is no filler 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?
For a tool with two numeric parameters, no annotations, no output schema, and a trivial operation, the description provides all necessary context: what the inputs are, what the tool does, and what the caller receives. Nothing an agent needs to invoke it correctly is missing.
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 only provides names and types (a, b as numbers), with 0% description coverage. The description compensates by clarifying that both parameters are the two addends and that the result is their sum, which gives functional meaning beyond the raw schema. It could only be improved by explicitly naming the parameters.
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 states a specific verb ('Adds'), the resource ('two numbers'), and the outcome ('returns the sum'). It is not a tautology of the name and clearly distinguishes this tool from the sibling tools echo and server_time.
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 the clear context: use this tool when you need to add two numbers and get their sum. While it doesn't explicitly exclude siblings, none of them perform arithmetic, so the context is unambiguous and no exclusions are needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
echoEchoAInspect
Echoes the provided text back to the caller.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to echo back |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It clearly conveys the core behavior and result, implying no state change. However, it does not explicitly address formatting, length limits, or edge cases, leaving a minor transparency gap.
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 sentence front-loads the action and result with zero filler. Every word contributes to understanding the tool.
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 one-parameter echo tool with no output schema, the description fully suffices: it tells the agent what the tool does and what it returns. No additional context is necessary.
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 already documents the single 'text' parameter with 100% coverage. The description adds no meaning beyond what the schema provides, so baseline 3 applies.
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?
States a specific verb ('Echoes'), a resource ('the provided text'), and a destination ('back to the caller'). Clearly distinguishable from sibling tools add and server_time.
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 the tool is for repeating text back, but it offers no explicit when-to-use guidance, alternatives, or exclusions. For a trivial tool the context is self-evident, but no direct usage guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
server_timeServer timeAInspect
Returns the current server time (ISO 8601, UTC).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It adequately conveys that this is a read-only retrieval operation ('returns') and specifies the output format and timezone (ISO 8601, UTC), which is valuable behavioral context.
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, front-loaded sentence provides complete information without any filler. Every word earns its place.
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 zero-parameter utility with no output schema, the description is fully sufficient: it states what the tool returns and the exact format of that return value. No additional context is needed for an agent to call it correctly.
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 zero parameters and the schema is empty, so there are no parameter semantics to document. The description appropriately confirms that calling the tool requires no 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?
The description states a specific verb and resource: it returns the current server time in ISO 8601 UTC format. This clearly distinguishes it from siblings add and echo, which perform unrelated operations.
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 makes the intended use clear: call this tool whenever the current server time is needed. There are no time-related sibling tools requiring exclusions, so no explicit alternative guidance is necessary.
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.
3 tool updates
- First observed
add - First observed
echo - First observed
server_time
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