deploy-mcp
Server Quality Checklist
Latest release: v0.6.5
- Disambiguation5/5
Each tool has a clearly distinct purpose: status checking, streaming progress, comparing deployments, fetching logs, and listing projects. No two tools overlap in function.
Naming Consistency5/5All tool names follow the same verb_noun pattern (check_, watch_, compare_, get_, list_) with snake_case, making the API predictable and easy to navigate.
Tool Count5/5Five tools is a well-scoped set for a deployment monitoring server, covering all core activities without bloat.
Completeness4/5The tool surface covers status, live progress, logs, and comparisons, but lacks a way to list historical deployments for a project, which would be useful for selecting deployments to compare.
Average 3.3/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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, the description carries the full burden for behavioral disclosure. 'Check' conveys a read-only operation, but it does not mention authentication requirements, rate limits, pagination, or the response structure beyond 'status'. This is minimal disclosure for a tool with no annotation safety net.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler or redundant repetition of the tool name. Every word contributes meaning ('Check', 'latest', 'deployment status', 'project', 'platform').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, yet the description does not explain the return format, how multiple deployments are returned, or authentication behavior. Given the tool has four parameters and sits alongside related siblings, one sentence is insufficient for an agent to fully predict invocation results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are already well documented (platform enum, project name/ID, optional token, limit with default/max). The description adds only the 'latest' scope, which aligns with the limit default of 1 but does not provide additional semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and resource ('deployment status') with scope ('latest', 'for a project on a platform'), clearly distinguishing it from log or comparison tools. It loses one point because 'latest' singular conflicts with the `limit` parameter allowing up to 20 results, making the scope slightly ambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given about when to use this tool versus siblings like watch_deployment or get_deployment_logs. The description implies usage through its verb but provides no prerequisites, exclusions, or alternative recommendations.
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 present, so the description carries the full burden. It does disclose that results are limited to projects the user has access to, but it incorrectly says 'all' when the limit parameter caps results (default 20, max 100). It also does not mention read-only behavior or authentication requirements beyond the schema's token parameter. The 'all' claim is misleading and lowers transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action and resource. There is no wasted wording, and it is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool, the schema fills in parameter details, but the description leaves gaps: it does not state what the return value looks like (e.g., an array of objects), and the 'all' claim conflicts with the limit parameter. The relationship to sibling tools is absent. It is minimally complete but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover 100% of parameters with detailed info (limit range, token purpose, platform enum). The description itself adds no parameter-level detail, so the baseline of 3 applies. It does not explain how 'all' relates to the limit parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('projects/sites'), and scopes it to 'a platform that you have access to'. It distinguishes itself from the sibling tools (check_deployment_status, watch_deployment, etc.) by being the only listing/discovery tool. The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 the sibling tools. It does not mention that this is a prerequisite for other deployment-related tools, nor does it give context about when listing projects is appropriate. Usage is only implied by the name.
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 must disclose behavioral traits. It mentions identifying changes and issues, but it does not state whether the operation is read-only, what output format to expect, authentication requirements, or any side effects. This leaves significant gaps for an agent trying to predict the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the action and resource, and it lacks filler or redundant phrasing. Every element conveys useful information about what the tool does, making it appropriately concise for its purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 8 parameters, 5 modes, no output schema, and no annotations, making it fairly complex. The description does not enumerate the comparison modes, explain mode-specific parameter dependencies, or describe the return value structure. The schema covers parameter definitions, but the high-level context—what gets compared, how results are presented, and operational requirements—is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% parameter description coverage, so the baseline is 3. The description adds only a vague reference to 'smart comparison modes' and high-level outcomes, but does not provide param-specific details beyond the schema. Thus, it neither improves nor significantly detracts from the schema's already clear parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Compare deployments') with a defined resource and purpose ('identify changes, performance differences, and potential issues'). This distinguishes it from sibling tools like check_deployment_status, watch_deployment, and get_deployment_logs, which focus on single-deployment status, watching, and logs rather than comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for comparing deployments, but it does not explicitly state when to prefer it over alternatives or when not to use it. No sibling tools are referenced, and there is no 'use this for comparison, not for single-deployment checks' guidance. The usage context is implied but not overt.
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 the full burden. It omits behavior such as authentication requirements (token parameter), default filter behavior (error), and the special 'latest' deploymentId handling that requires a project. The description only says 'Fetch detailed logs', leaving significant behavioral context undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It states the action and purpose efficiently. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, so the description should explain return values or constraints. It does not mention that logs are filtered by default, that 'latest' requires a project, or the structure of the log output. This is inadequate for a tool with 5 parameters and multiple platforms.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters have their own descriptions. The tool description adds no extra meaning beyond schema; e.g., 'specific deployment' aligns with deploymentId but does not clarify the 'latest' option or filter defaults. Baseline 3 applies because the schema already documents parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource 'detailed logs for a specific deployment'. It distinguishes this from siblings like check_deployment_status (status) and compare_deployments (comparison) by focusing on log retrieval for debugging.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'useful for debugging failed deployments' implies when to use it, but it does not explicitly mention alternatives or when not to use it. Sibling tools exist (watch_deployment, check_deployment_status) but are not referenced, so the guidance remains implicit rather than directive.
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 must carry full behavioral disclosure. It mentions streaming and error info, but does not state whether the tool is read-only, how long it runs, whether it blocks, or what happens when the deployment finishes. This is a significant gap for a streaming tool without annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that directly communicates the tool's purpose without any fluff or redundant information. Every word earns its place, and it is appropriately sized for the tool's functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (streaming behavior) and lack of an output schema, the description is too sparse. It does not explain the structure of the stream, how to terminate it, or what 'detailed status updates' entails. Without annotations or output schema, the description should provide more context to be complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all parameters with descriptions (100% coverage), so the description adds no additional parameter-level meaning. Baseline of 3 is appropriate since the schema already documents parameter purposes, and the description does not enhance or clarify them further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('stream') and resource ('deployment progress'), and specifies it includes status updates and error information. This distinguishes it from sibling tools like check_deployment_status, which implies a one-time status check rather than continuous streaming.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The context of 'real-time streaming' clearly implies when to use it (for continuous monitoring of deployments), but it lacks explicit exclusions or alternatives. There is no mention of when not to use it or a direct comparison to siblings like check_deployment_status or get_deployment_logs.
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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- Evaluate tool definition quality.
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