io.github.zomma-dev/quantcontext

MCPcommunity
v0.1.2io.github.zomma-devUnknownUpdated 5mo agoGitHub

Deterministic stock screening, backtesting, and factor analysis for AI trading agents

QuantContext is an MCP server that turns plain-English strategy descriptions into executable quant research: screen stocks by any criteria, backtest over historical data, and run factor analysis to see where the returns come from. Every number is computed from real market data, not generated by an LLM. Results are fully reproducible. Works with Claude, Codex, OpenCode, or any other MCP-compatible…

Automatically indexed from public sources. Not yet verified by the developer on Forge.Claim this listing →
5mo agoLast update
Package
Authorio.github.zomma-dev
LicenseUnknown
Version0.1.2
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
Included automatically when the publisher runs `forge publish`
Domain verification+0/5
Publisher: host /.well-known/forge.json on the package homepage with { "publisher": "<github-login>" }
npm Trusted Publishing (Sigstore)+0/5
Publish from GitHub Actions with --provenance so the attestation binds this package to this repo
npm maintainer match+0/5
Earned once your identity is verified above and that login is an npm maintainer of this package
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✓ Cleanv0.1.2 · 2mo ago
EvalsNone
IndexedJun 13, 2026

Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts — it cannot prove the absence of malicious code.

About

QuantContext is an MCP server that turns plain-English strategy descriptions into executable quant research: screen stocks by any criteria, backtest over historical data, and run factor analysis to see where the returns come from. Every number is computed from real market data, not generated by an LLM. Results are fully reproducible. Works with Claude, Codex, OpenCode, or any other MCP-compatible coding agent. No API keys. No configuration. Three tools that compose into a full research…

Keywords
mcp