io.github.kimsb2429/internal-knowledge-base

MCPcommunity
v0.1.0io.github.kimsb2429UnknownUpdated 5mo agoGitHub

Production-ready RAG + MCP demo: eval-in-CI merge gate, Langfuse traces, structure-aware chunking.

A public Retrieval-Augmented Generation pipeline exposed as an MCP server. Sample content from Veterans Affairs education manuals. The repo implements evaluation, observability, and structure-aware ingestion. Cost/latency tuning, tenant-level access control, and other production concerns are discussed in the article linked below. 📖 Full writeup in Towards AI: Enterprise Internal Knowledge Base…

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5mo agoLast update
Package
Authorio.github.kimsb2429
LicenseUnknown
Version0.1.0
Sourcemcp-registry
GitHubkimsb2429/internal-knowledge-base
SBOMCycloneDX 1.6 ↓
Trust Status
B
60/100Good
✓Listed in Forge index+10/10
—Publisher identity verified+0/30
→ Publisher: run `forge publish` from the repo to claim ownership
—Domain verification+0/10
→ Not currently available for this listing type — the domain-verification check only runs for npm-backed packages today, so this row cannot be earned here yet regardless of what's hosted at the domain.
✓Prompt-injection scan · clean+30/30
✓Obfuscation / exfil scan · 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✓ CleanvHEAD · 3mo agoHow well does this scan work?
EvalsNone
IndexedJun 13, 2026

Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts.

Tools

Source not readable3mo ago

The repository archive could not be read at scan time (The operation was aborted due to timeout), so no tool declarations could be extracted from it. Nothing here is a statement about what this exposes.

About

A public Retrieval-Augmented Generation pipeline exposed as an MCP server. Sample content from Veterans Affairs education manuals. The repo implements evaluation, observability, and structure-aware ingestion. Cost/latency tuning, tenant-level access control, and other production concerns are discussed in the article linked below. 📖 Full writeup in Towards AI: Enterprise Internal Knowledge Base RAG MCP: POC-to-Production RAG demos tend to focus on the quality of the retrieval pipeline, without…

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