MCP Terminal

by h004888

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: get_logs retrieves logs, list_processes enumerates processes, search_logs filters logs, start_process initiates processes, and stop_process terminates them. The descriptions reinforce these boundaries, making misselection unlikely.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern (e.g., get_logs, list_processes, search_logs, start_process, stop_process), using snake_case throughout. This predictability aids agent comprehension and tool selection.
Tool Count5/5
With 5 tools, the set is well-scoped for terminal/process management, covering core operations (list, start, stop processes, and get/search logs). Each tool earns its place without bloat or thinness.
Completeness4/5
The tools provide strong coverage for process lifecycle (start, stop, list) and log handling (get, search), but minor gaps exist, such as no tool for restarting processes or managing log files (e.g., delete/rotate). Agents can work around this with existing tools.
Average 2.9/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 states 'Get logs' but doesn't specify if this is read-only, requires permissions, has rate limits, returns structured or raw data, or handles errors. For a tool with no annotations, this leaves significant gaps in understanding its behavior and constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, making it easy to parse. However, it could be more front-loaded with key details (e.g., scope or differentiation), but its brevity is appropriate for basic clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what the logs contain, how they're formatted, or any behavioral traits, leaving the agent under-informed for proper invocation and result handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting 'id' as 'Process identifier' and 'lines' as 'Number of lines to return (optional)'. The description adds no additional meaning beyond this, such as format examples or constraints, but the schema provides adequate baseline information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get logs from a process' clearly states the verb ('Get') and resource ('logs from a process'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'search_logs' or specify what type of logs or scope (e.g., recent, all, error logs), leaving it somewhat vague compared to alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives like 'search_logs' or 'list_processes'. It doesn't mention prerequisites (e.g., needing a process ID from 'list_processes') or exclusions (e.g., not for real-time monitoring), leaving the agent with minimal context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'search' implies a read operation, the description doesn't disclose important behavioral traits like whether this requires authentication, has rate limits, returns paginated results, or what happens with invalid inputs. It provides minimal context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a search tool and front-loads the essential information. Every word earns its place by contributing to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a search operation that likely returns complex results, the description is insufficient. It doesn't explain what format results come in, whether they're filtered/ranked, error conditions, or performance characteristics. For a search tool with 3 parameters and no structured output documentation, more context is needed about the operation's behavior and results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description mentions 'keyword or regex' which aligns with the 'keyword' parameter description, but adds no additional semantic context beyond what's in the schema. With complete schema coverage, the baseline of 3 is appropriate as the description doesn't significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('search') and resource ('logs'), and specifies the search target ('keyword or regex'). It distinguishes from sibling 'get_logs' by implying filtering/searching rather than retrieval, but doesn't explicitly differentiate. The description is not tautological and provides meaningful information about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives like 'get_logs' or 'list_processes'. There's no mention of prerequisites, context for usage, or exclusions. The agent must infer usage from the tool name and description alone without any explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 that the process is 'long-running' and output is captured to a log file, but fails to address critical aspects like permissions required, whether the process runs asynchronously, how errors are handled, or if there are rate limits. This leaves significant gaps for safe and effective tool invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 unnecessary words. It is front-loaded with the core action and outcome, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of starting a process (which involves execution, logging, and potential side-effects) and the absence of annotations and output schema, the description is insufficient. It does not explain what the tool returns (e.g., process status, log file path), error conditions, or interaction with sibling tools like 'get_logs', leaving the agent with incomplete operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters (id, command, cwd). The description does not add any additional meaning or context beyond what the schema provides, such as examples of valid commands or log file naming conventions. Baseline 3 is appropriate as the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Start a long-running process') and the outcome ('capture its output to a log file'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'stop_process' or 'list_processes', which would require mentioning process lifecycle management or monitoring aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives such as 'stop_process' or 'get_logs'. It lacks context about prerequisites, error handling, or typical use cases, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('stop') but doesn't clarify what 'stop' entails—whether it's a graceful shutdown, force termination, or reversible. It also omits critical details like permissions required, side effects (e.g., data loss), error handling, or confirmation prompts. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, achieving maximum efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation to stop processes), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like safety, reversibility, or response format, leaving significant gaps for an AI agent to understand how to invoke it correctly in context with its siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'id' documented as 'Process identifier to stop'. The description adds no additional meaning beyond this, such as format examples (e.g., numeric ID, name) or where to obtain the ID (e.g., from 'list_processes'). Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('stop') and target resource ('a running process'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'start_process' beyond the obvious verb difference, nor does it specify what type of process (e.g., system process, background job) it operates on.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives. It doesn't mention prerequisites (e.g., the process must be running), when not to use it (e.g., for system-critical processes), or how it relates to siblings like 'list_processes' (to identify processes to stop) or 'start_process' (to restart after stopping).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the action ('List all running processes') but lacks details on permissions, rate limits, output format, or whether it's a safe read operation. This is insufficient for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic action but lacks details on behavior and output, which are important for completeness even in simple tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 fully documents the absence of inputs. The description doesn't need to add parameter information, and it appropriately doesn't mention any, earning a baseline score near the top of the scale.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('running processes managed by this MCP server'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_logs' or 'search_logs', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'get_logs' or 'search_logs'. The description implies usage for listing processes but offers no context on prerequisites, timing, or exclusions.
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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