generate-data-mcp

by ns-3e

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool serves a distinct function: generating data, generating full projects, checking API usage, retrieving field options, listing fields, listing projects, proposing schemas, and refining schemas. No overlapping purposes.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with lowercase and underscores (e.g., generate_data, list_field_types). No mixing of styles.
Tool Count5/5
With 8 tools, the set is well-scoped for the domain of synthetic data generation and schema management. It covers both creation and configuration without being overwhelming.
Completeness4/5
The tool set covers core workflows: generating data and projects, schema proposal/refinement, and listing field types and projects. Minor gaps exist (e.g., no delete or update for projects), but agents can still accomplish main tasks.
Average 3/5 across 8 of 8 tools scored. Lowest: 2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 7 commits in the last 12 weeks
- No stable releases found
- 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.
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}
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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 full responsibility for behavioral disclosure. It mentions 'conversation' but does not explain iterative behavior, side effects, authentication requirements, or any constraints. The single sentence is insufficient for a tool with two complex parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words) but at the cost of essential detail. Given the tool's complexity (two required nested objects), the description should be longer and front-load critical information. The brevity is more under-specification than efficient conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema but the description ignores it. With 0% schema parameter coverage, no usage guidelines, and minimal behavioral context, the description is grossly incomplete for an agent to use this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation for the 'messages' or 'current_schema' parameters. The agent receives no guidance on format, purpose, or constraints beyond the schema's structural definitions.
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 states 'Refine an existing schema via conversation,' which identifies a specific verb and resource. However, it does not differentiate from the sibling tool 'propose_schema' and lacks detail on what 'refine' entails (e.g., field additions, type changes).
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 given on when to use this tool versus alternatives like 'propose_schema' or 'generate_data.' The phrase 'via conversation' implies interactivity but provides no explicit context or exclusions.
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 carries full burden. It mentions return type (CSV/text or error) but lacks details on side effects, safety, or operational constraints like memory or API limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with purpose. Could be more structured with separate sections for return value and parameter details.
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 4 parameters, no schema descriptions, no annotations, but an output schema exists (not shown). Description fails to explain parameter usage or provide sufficient context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no parameter descriptions). Description only hints at format via 'CSV/text' but does not explain fields, num_rows, or settings, leaving agents uninformed.
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?
Clear verb ('generate') and resource ('synthetic data rows'). Distinguishable from siblings like generate_project and data retrieval tools. However, could be more specific about the type of synthetic data.
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 on when to use this tool versus alternatives. Does not mention prerequisites or exclusion criteria.
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 must fully disclose behavioral traits. It only states the action but omits any side effects, permissions, idempotency, rate limits, or return behavior beyond what output schema might cover. This is insufficient.
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 sentence, front-loaded with the core action. It is concise with no wasted words, though it may be too brief.
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 has a sibling 'refine_schema' and two parameters (one required), the description lacks necessary context such as how the tool differs from alternatives, the expected input style, and any limitations. The presence of an output schema partially compensates for return value explanation, but overall completeness is low.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the schema properties lack any descriptions. The tool description does not explain the purpose or format of the 'prompt' and 'locale' parameters, failing to compensate for the missing schema coverage.
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 (propose) and resource (schema) and the source (natural language). However, it does not distinguish the tool from its sibling 'refine_schema', which could cause confusion. Thus, purpose is clear but lacks sibling differentiation.
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, nor any prerequisites or exclusions. The single sentence offers no usage context.
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 provided, so description carries full burden. It discloses return format (ZIP bytes as text or JSON error) but does not mention if the operation is destructive, requires permissions, or side effects.
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 concise with one sentence for purpose and one for output. However, it could include more detail without excessive length.
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?
For a tool that generates tables, the description lacks information on what 'generate' entails (creates new? overwrites?), limits, and output schema specifics. The presence of an output schema is noted but not leveraged.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but description adds no detail about parameters. The 'format' parameter defaults to 'zip' but possible values are unexplained; 'project_id' is not contextualized beyond being required.
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 states 'Generate all tables in a Project' which is a specific verb and resource, distinguishing it from sibling 'generate_data' which likely operates on individual tables. However, it does not explicitly contrast with siblings.
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 on when to use this tool versus alternatives like 'generate_data' or 'list_projects'. The description only states what it does, not the context or prerequisites.
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 bear the full burden. It does not disclose any behavioral traits such as read-only nature, authentication needs, or side effects. The description is too minimal to be informative.
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 sentence with no wasted words. It is appropriately short, though it could benefit from slight expansion without losing conciseness.
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?
The tool has one simple parameter and an output schema exists, so the description does not need to explain return values. However, it provides no additional context about field types, usage patterns, or integration with sibling tools, leaving room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero description coverage, and the tool description adds no parameter-specific information. The 'field_type' parameter is unexplained, leaving the agent without knowledge of valid values or where to obtain them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get configuration schema for a field type', specifying a concrete verb and resource. It distinguishes from siblings like 'list_field_types' which lists types rather than their schemas.
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 on when to use this tool versus alternatives like 'list_field_types' or 'propose_schema'. The agent is left to infer the appropriate context.
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, the description must convey behavioral traits. It only states 'current' implying real-time, but omits details like read-only nature, error conditions, or data freshness. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no extraneous words. Every word earns its place.
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?
While the output schema exists and explains return values, the description lacks behavioral details such as whether the key must be active or how historical usage is handled. Adequate for a simple tool but with gaps.
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?
There are no parameters, so the schema coverage is 100%. The description adds nothing parameter-specific, but baseline for 0 params is 4. No additional meaning needed.
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 'Get' and resource 'API key usage stats', making the purpose obvious. However, it does not differentiate from sibling tools like 'generate_data' or 'list_projects', which are distinct but not contrasted.
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. For a simple read operation, this may not be critical, but the absence of context about usage scenarios lowers the score.
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, and description lacks behavioral details like read-only nature, pagination, limits, or authentication needs. The description carries full burden but is too minimal.
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?
Single sentence, front-loaded, no wasted words. Efficiently conveys purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and existence of output schema, the description sufficiently states what the tool does. However, it lacks mention of any implicit behavioral aspects like project scope or limitations, but overall adequate.
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?
No parameters exist, so schema coverage is 100%. Description adds minimal context ('Premium') beyond the schema. Baseline 4 is appropriate as there is nothing to explain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'List user's Projects (Premium)' with specific verb and resource, and adds context about the feature tier. It is unambiguous and distinct from sibling tools which focus on different resources.
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 on when to use this tool vs alternatives. Does not mention prerequisites, such as authentication or project access, nor any exclusions.
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?
With no annotations, the description solely conveys the behavior: listing field types grouped by category. It is accurate but does not disclose possible side effects, auth needs, or rate limits. The description is sufficient for a simple read 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 sentence with no wasted words. It is front-loaded with the action verb 'List'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no parameters and an output schema exists, so the description's mention of grouping by category suffices. However, it could note that it is read-only or provide example categories for better completeness.
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?
As there are no parameters and schema coverage is 100%, the description adds value by explaining the output grouping, but it doesn't add parameter-specific detail. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and clearly identifies the resource as 'field types' with the additional detail of grouping by category. It distinguishes the tool from siblings like get_field_options which likely gets options for a specific field, not a general list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (need to see available field types), but provides no explicit when-not-to-use or alternatives. It is adequate but lacks depth.
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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