Dataparity
NPM · DATAPARITY
Cross-database data diff and reconciliation for AI agents, with a portable row hash
Available components
Last scanned (5 hours ago)
Scores higher than 40% of npm servers
Category Databases
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 Security98
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- 37 of 127 dependencies flagged as unhealthy. View diagnostics → Partial
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 5 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability81
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 406 tokens (~81/item across 5 items; 4 tools + 1 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
- Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 4 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 5 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
Unverified: 1 category
A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.
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.
- 31 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- Security disclosure: unverified → fail ▼ functional
- 30 Oct 26 56
First indexed and scored.
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 5 Nov 2026 · Analysed npm/dataparity@0.1.0
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Background: How many MCP packages publish verified provenance →
Dependencies 127 packages
| Packages resolved | 127 |
|---|---|
| Stale | 37 |
| 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 →
dataparity_describe_table ~61
Describe one table: its columns, their types and whether they are nullable. Use this to choose key columns and comparison columns.
| Name | Type | Req | Description |
|---|---|---|---|
| source | string | yes | The configured source name. |
| table | string | yes | The table name, optionally schema-qualified. |
No output schema declared.
No examples provided.
dataparity_diff ~238
Compare two tables and report what changed. Works across different databases: both sides compute the same canonical row hash, so only hashes are compared, never raw data. Returns added, removed and modified rows, schema differences, a risk verdict, and the segments of data where the changes concentrate.
| Name | Type | Req | Description |
|---|---|---|---|
| columns | array | – | Columns to compare. Defaults to every column the two tables share. |
| format | string | – | Output format. Defaults to json. |
| key_columns | array | yes | Columns used to match rows across the two sides. |
| left | string | yes | The left source name. |
| left_table | string | yes | The table on the left. |
| max_attributions | number | – | Maximum number of attribution segments to return. Defaults to 5. |
| max_changes | number | – | Maximum number of row changes to return. Defaults to 100. |
| right | string | yes | The right source name. |
| right_table | string | yes | The table on the right. |
| sample | boolean | – | Compare only a sample of rows. The result is marked as sampled. |
| where | string | – | A WHERE expression applied to both sides. |
No output schema declared.
No examples provided.
dataparity_list_sources ~31
List the configured data sources that can be diffed. Returns each source name, engine type and label.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
dataparity_list_tables ~61
List the tables in a configured source, with their columns. Use this to find the right table and key columns before diffing.
| Name | Type | Req | Description |
|---|---|---|---|
| schema | string | – | Optional schema to restrict the listing to. |
| source | string | yes | The configured source name. |
No output schema declared.
No examples provided.
How do I install the Dataparity MCP server?
Dataparity runs locally as an npm package, launched with npx -y dataparity. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · dataparity
claude mcp add arif-js-dataparity -- npx -y dataparity
What is the Dataparity MCP server?
Dataparity is an MCP server listed in the public MCP registry as io.github.arif-js/dataparity. Cross-database data diff and reconciliation for AI agents, with a portable row hash. This page covers its npm package (dataparity).
Is the Dataparity MCP server safe to use?
Dataparity scores 71 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. It declares no install or post-install scripts. 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 Dataparity MCP server expose?
Dataparity exposes 4 tools: dataparity_list_sources, dataparity_list_tables, dataparity_describe_table, dataparity_diff. Their descriptions and schemas cost roughly 391 tokens of context every time the server is loaded.
Is the Dataparity MCP server still maintained?
Dataparity is still listed as active in the MCP registry. We last reached this channel on 5 November 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 Dataparity MCP server under?
Dataparity declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.