io.github.rasinmuhammed/misata

MCPcommunity
v0.8.0.post1io.github.rasinmuhammedUnknownUpdated 4mo agoGitHub

Complete package for synthetic data generation.

Realistic multi-table synthetic data that conforms to the outcome you specify exact revenue curves, fraud rates, and referential integrity, from a sentence, YAML, or your own database. No ML model, no real data. Most synthetic-data tools learn from a real dataset and imitate it. Misata works the other way: you declare the outcome you want : "monthly revenue rises from \$50k to \$200k," "fraud is…

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68GitHub stars
4Forks
4mo agoLast update
Package
Authorio.github.rasinmuhammed
LicenseUnknown
Version0.8.0.post1
Sourcemcp-registry
Trust Status
B
60/100Good
✓Listed in Forge index+10/10
—Publisher identity verified+0/20
→ Publisher: run `forge publish` from the package repo to claim ownership
—Ed25519 publish signature+0/5
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—Domain verification+0/5
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—npm maintainer match+0/5
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✓CVE scan · clean+30/30
✓Static analysis · clean+20/20
Paste into Claude Code, Cursor, or any AI assistant to fix all gaps
StatusCommunity-indexed
PublisherUnverified
SignatureUnsigned
Domain—
Provenance—
DependenciesNot audited
Tool surface—
Security scan✓ Cleanv0.8.0.4 · 3mo agoHow well does this scan work?
EvalsNone
IndexedJun 13, 2026

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Tools

No tool declarations found in the source3mo ago

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About

Realistic multi-table synthetic data that conforms to the outcome you specify exact revenue curves, fraud rates, and referential integrity, from a sentence, YAML, or your own database. No ML model, no real data. Most synthetic-data tools learn from a real dataset and imitate it. Misata works the other way: you declare the outcome you want : "monthly revenue rises from \$50k to \$200k," "fraud is 3% in Q1 rising to 8% by Q4," "every customer's equals the sum of their orders" — and Misata…

Keywords
mcp
Alternatives
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No dependency coverage

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