@rendershot/mcp-server
OfficialServer Quality Checklist
Latest release: v0.1.5
- Disambiguation5/5
Each tool has a clear, distinct purpose: bulk_render for batch jobs, check_balance for credits, generate_pdf and take_screenshot for single outputs. No overlap.
Naming Consistency5/5All tools use consistent snake_case with verb_noun pattern (bulk_render, check_balance, generate_pdf, take_screenshot).
Tool Count5/54 tools is well-scoped for a focused rendering server, covering single and batch operations plus balance checking without unnecessary extras.
Completeness4/5Covers core rendering tasks (screenshot, PDF, batch) and account monitoring. Minor gap: no way to manage or cancel batch jobs, but results are returned immediately.
Average 3.4/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions the basic output format (base64) but omits important details such as maximum page size, render timeouts, or that the 'ai_cleanup' parameter consumes credits. The description lacks transparency about side effects or constraints.
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 very concise: two sentences that front-load the core functionality. No unnecessary words or repetition.
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 (12 parameters, enums, nested objects, no output schema, no annotations), the description is too sparse. It fails to explain return values when 'output_path' is omitted, credit costs, or error conditions. A more complete description would include these details.
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 description does not need to add much. The description only restates the tool's purpose and does not elaborate on parameter meaning beyond what the schema already provides. This meets the baseline for high coverage.
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 clearly states the tool's function: generate a PDF from a web page or HTML and returns it as base64. While it distinguishes from siblings like 'take_screenshot' (different output format) and 'check_balance' (unrelated), it does not explicitly differentiate from 'bulk_render' which may have overlapping functionality.
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 alternatives like 'bulk_render' or 'take_screenshot'. It does not mention prerequisites, limitations, or context for choosing one tool over another.
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 provided, so description must disclose behavioral traits. It doesn't mention non-destructiveness, credit consumption, or failure modes. Only states basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with key information front-loaded. No fluff, but could be slightly more structured.
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?
Description omits crucial context like requirement for exactly one of url or html, optional save to file, and cookie handling. Given 14 parameters and no output schema, more context is needed.
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 coverage is 100% with detailed descriptions; description adds nothing beyond stating the return format. Baseline 3 is appropriate.
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?
Description clearly states verb 'capture' and resource 'screenshot of a web page or HTML content', and mentions return format. Distinguishes from siblings by specifying both URL and HTML content options.
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 on when to use this tool vs alternatives like bulk_render or generate_pdf. The description does not compare or contrast with siblings.
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. It mentions returning base64-encoded output but does not disclose potential side effects, rate limits, authentication requirements, or whether the tool is read-only or destructive. Does not mention that output_dir saves files to the filesystem.
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?
Single sentence containing all essential information: batch size limit, supported render types, and return format. No unnecessary words or redundant details.
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?
The description is minimal given the tool's complexity (nested jobs with many options). No output schema exists, and the description does not explain the return structure beyond base64 encoding (e.g., per-job status, errors). The schema covers input params adequately but the description could provide more context about the response format.
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% with detailed descriptions for each parameter and nested object. The description adds no new meaning beyond what is already in the schema, meeting the baseline of 3.
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?
Description clearly states it submits up to 20 screenshot or PDF render jobs in a single request and returns base64-encoded results. This distinguishes it from siblings like take_screenshot and generate_pdf which are singular operations.
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?
Implicitly suggests usage for batch operations by mentioning 'up to 20 jobs in a single request', but lacks explicit guidance on when to use this tool versus the singular alternatives. No when-not or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
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 states it checks credits and plan details, which is a read-only operation, but does not explicitly confirm no side effects. For a simple check tool, this is minimally adequate.
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, clear sentence with no wasted words. It is front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has zero parameters, no output schema, and is a simple status check, the description is complete. It tells the agent what the tool does and what information it returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, and schema coverage is 100%. The description does not need to add parameter meaning as there are none. Baseline of 4 is appropriate.
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 uses a specific verb 'check' and identifies the resources 'remaining API credits' and 'current plan details', clearly distinguishing it from sibling tools like bulk_render and generate_pdf which are for generating PDFs and screenshots.
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 usage for checking credits and plan, but does not explicitly state when to use or not use this tool versus alternatives. However, given the siblings are unrelated, the usage context is clear enough.
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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