Generate-Data
PYPI · GENERATE-DATA-MCP · SCANNED SEP 21
MCP server for Generate-Data.com: dataset generation, AI schema design, Project management.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 0 of 29 dependencies flagged as unhealthy. View diagnostics → Pass
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 48 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability69
- AI-judged instruction clarity (good).Pass
- Context-footprint check failed: tool/resource definitions use about 1058 tokens (~151/item across 7 items; 7 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management90
- Stability observed for 27 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 7 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 7 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the Generate-Data MCP server?
Generate-Data runs locally as a PyPI package, launched with uvx generate-data-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · generate-data-mcp
claude mcp add ns-3e-generate-data-mcp -- uvx generate-data-mcp
{
"mcpServers": {
"ns-3e-generate-data-mcp": {
"command": "uvx",
"args": [
"generate-data-mcp"
]
}
}
} {
"servers": {
"ns-3e-generate-data-mcp": {
"command": "uvx",
"args": [
"generate-data-mcp"
]
}
}
} codex mcp add ns-3e-generate-data-mcp -- uvx generate-data-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"ns-3e-generate-data-mcp": {
"type": "local",
"command": [
"uvx",
"generate-data-mcp"
],
"enabled": true
}
}
} openclaw mcp add ns-3e-generate-data-mcp --command uvx --arg generate-data-mcp
mcp_servers:
ns-3e-generate-data-mcp:
command: "uvx"
args: ["generate-data-mcp"] {
"McpServers": {
"ns-3e-generate-data-mcp": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"generate-data-mcp"
]
}
}
} assistant mcp add ns-3e-generate-data-mcp -t stdio -c uvx -a generate-data-mcp
{
"mcpServers": {
"ns-3e-generate-data-mcp": {
"command": "uvx",
"args": [
"generate-data-mcp"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 21 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 19 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.
- 18 Sept 26 −3
- Stability: pass → 0.80 functional
- 17 Sept 26 0
- Stability: 0.97 → pass security
- 16 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 15 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 14 Sept 26 −14
- Malware scan: pass → unverified ▼ security
- 12 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 21 Sept 2026 · Analysed pypi/generate-data-mcp@2.0.1
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 29 packages
| Packages resolved | 29 |
|---|---|
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
gd_design_schema ~237
Design a dataset schema from natural language — one tool for both the first proposal and follow-up refinements. Behavior branches on args: - First call (propose): pass only `prompt` (and optionally `locale`, e.g. 'en_US', 'fr_FR'). `messages`/`current_schema` left unset. - Refine call: pass BOTH `messages` (the running conversation, list of `{"role": "user"|"assistant", "content": str}`) AND `current_schema` (the schema object returned by the prior call) together — `prompt` is still required by the signature but is not sent upstream for a refine call. If only one of `messages`/`current_schema` is set, this falls back to propose using `prompt`. Returns the proposed/refined schema in `data` (upstream `proposed_schema` shape), ready to hand to `gd_generate_dataset` as `fields`.
| Name | Type | Req | Description |
|---|---|---|---|
| current_schema | – | – | – |
| locale | string | – | – |
| messages | – | – | – |
| prompt | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
gd_generate_dataset ~241
Generate synthetic dataset rows from a field list. Use this when the user wants actual generated data (as opposed to schema design or field-type discovery). `fields` is a list of `{"name": str, "type": str, "options": dict}` (get valid `type` values from `gd_list_field_types`/`gd_get_field_type_options`). `format` must be one of `csv`, `json`, `xml`, `parquet`, `zip` (anything else returns an `unsupported_format` error). `num_rows` caps upstream row count; `settings` is an optional passthrough dict of generation settings. Returns the JSON envelope: on success `data.content` (csv/json/xml) or `data.content_base64` (parquet/zip, base64-encoded — never decode these as utf-8) plus `data.size_bytes`/`data.truncated`. On failure returns a corrective error envelope (never raises).
| Name | Type | Req | Description |
|---|---|---|---|
| fields | array | yes | – |
| format | string | – | – |
| num_rows | integer | – | – |
| settings | – | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
gd_generate_project ~192
Generate all tables in a Project and download the result (Premium tier only). `project_id` must be a positive integer (get one from `gd_list_projects`). `format` must be one of `csv`, `json`, `xml`, `parquet`, `zip` (default `zip`; anything else returns `unsupported_format`). Non-Premium API keys get a `tier_forbidden` error — upgrade the Generate-Data.com plan to use this tool. Returns the JSON envelope: on success `data.content` (csv/json/xml) or `data.content_base64` (parquet/zip, base64-encoded — never decode these as utf-8) plus `data.size_bytes`/`data.truncated`. On failure returns a corrective error envelope (never raises).
| Name | Type | Req | Description |
|---|---|---|---|
| format | string | – | – |
| project_id | integer | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
gd_get_field_type_options ~116
Get the configuration option schema for one field type (e.g. what options `email` or `date` accept). Use this before building a `fields` entry for `gd_generate_dataset` that needs non-default options. `field_type` must match `^[a-z0-9_]+$` (lowercase letters, digits, underscore only) — anything else returns `invalid_input` without calling upstream. Returns the option schema in `data`.
| Name | Type | Req | Description |
|---|---|---|---|
| field_type | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
gd_get_usage ~60
Get current API key usage stats (calls today, tier, limits). Use this to check remaining quota or confirm which tier the configured API key has before attempting a premium-only call. Takes no arguments. Returns the usage stats in `data`.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
gd_list_field_types ~65
List all available field types grouped by category. Use this to discover valid `type` values before calling `gd_generate_dataset` or to look up which category a field type belongs to. Takes no arguments. Returns the categorized field-type catalog in `data.categories`.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
gd_list_projects ~147
List the user's Projects (Premium tier only). Use this to discover `project_id` values before calling `gd_generate_project`. `limit` (default 20, max 100) and `offset` (default 0) page through the results; results are paginated client-side since the upstream API returns the full list. Non-Premium API keys get a `tier_forbidden` error — upgrade the Generate-Data.com plan to use this tool. Returns the page in `data` (`items`, `limit`, `offset`, `total_count`, `has_more`, `next_offset`).
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | – |
| offset | integer | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
What is the Generate-Data MCP server?
Generate-Data is an MCP server listed in the public MCP registry as io.github.ns-3e/generate-data-mcp. MCP server for Generate-Data.com: dataset generation, AI schema design, Project management. This page covers its PyPI package (generate-data-mcp).
Is the Generate-Data MCP server safe to use?
Generate-Data scores 80 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 21 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Generate-Data MCP server expose?
Generate-Data exposes 7 tools: gd_generate_dataset, gd_list_field_types, gd_get_field_type_options, gd_design_schema, gd_get_usage, and 2 more. Their descriptions and schemas cost roughly 1,058 tokens of context every time the server is loaded.
Is the Generate-Data MCP server still maintained?
Generate-Data is still listed as active in the MCP registry. We last reached this channel on 21 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the Generate-Data MCP server under?
Generate-Data declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.