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Search Merill's Weekly Microsoft AI Roundup (msai.ms) archive — curated weekly Microsoft AI news
Search Merill's Weekly Microsoft AI Roundup (msai.ms) archive — curated weekly Microsoft AI news
This is a well-structured MCP server for searching a public newsletter archive. The code is clean, authentication is properly optional (API key only needed for semantic search), and permissions are narrowly scoped to the server's purpose. Minor quality findings around error handling and input validation do not significantly impact the security posture. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.
5 files analyzed · 8 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-darrenjrobinson-microsoft-ai-roundup": {
"env": {
"OPENAI_API_KEY": "your-openai-api-key-here"
},
"args": [
"-y",
"microsoft-ai-roundup-mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
A Model Context Protocol (MCP) server for searching the archive of Merill's Weekly Microsoft AI Roundup — a curated weekly Substack newsletter by Merill Fernando (with Joshua Fernando) covering Microsoft AI: Copilot, GitHub, Azure AI, M365 AI integrations, and the surrounding ecosystem.
Ask natural-language questions like "When did Copilot get feature X?", "What did the roundup say about Build?", or "Which GitHub projects has it highlighted?" and get sourced answers with issue numbers, dates, and links.
Sister project to entra-news-mcp.
No installation, no API keys, no configuration required:
npx microsoft-ai-roundup-mcp
On first run the server downloads a pre-built search index (SQLite database) from this repo's GitHub Releases and caches it locally. It checks for an updated index at most once every 7 days.
Requires Node.js 22 or later — the server uses Node's built-in
node:sqlitemodule (no native dependencies). Node 20 will not work.
Add to claude_desktop_config.json:
{
"mcpServers": {
"microsoft-ai-roundup": {
"command": "npx",
"args": ["microsoft-ai-roundup-mcp"]
}
}
}
claude mcp add microsoft-ai-roundup -- npx microsoft-ai-roundup-mcp
{
"mcpServers": {
"microsoft-ai-roundup": {
"command": "npx",
"args": ["-y", "microsoft-ai-roundup-mcp"]
}
}
}
Keyword search works with zero configuration. For semantic (meaning-based) search, add an OpenAI API key:
{
"mcpServers": {
"microsoft-ai-roundup": {
"command": "npx",
"args": ["microsoft-ai-roundup-mcp"],
"env": { "OPENAI_API_KEY": "sk-..." }
}
}
}
Without a key the server degrades gracefully to keyword-only search.
| Tool | Description |
|---|---|
search_microsoft_ai_roundup | Search the full archive with natural language or keywords. Hybrid semantic + keyword search; returns sourced excerpts with issue number, date, and URL. Args: query (required), limit (default 10, max 50), mode (hybrid | semantic | keyword). |
get_issue | Retrieve the full content of an issue by issue_number or date (YYYY-MM-DD or YYYY-MM), with section headings preserved. |
list_issues | Browse the archive with optional year/month filtering and pagination. |
find_tool_mentions | Find community tools, GitHub projects, and Microsoft AI products/features mentioned across issues, with surrounding context. Optional query filter. |
Substack API (https://msai.ms/api/v1/posts)
│
▼
TypeScript ingestion script (scripts/ingest.ts)
│ weekly GitHub Action — Tuesdays 09:00 UTC
▼
OpenAI text-embedding-3-small embeddings (1536 dims)
│
▼
SQLite via node:sqlite (Node 22 built-in — no native deps)
│
▼
GitHub Release asset: microsoft-ai-roundup.db
│
▼
NPX MCP Server (stdio)
└─ Downloads DB on first run → caches in ~/.microsoft-ai-roundup-mcp/
└─ Re-checks for updates weekly (7-day staleness + tag diff)
└─ In-memory cosine similarity + SQL LIKE keyword search
Search implementation (honest version): semantic search loads all embedding vectors into memory at startup and ranks by cosine similarity in JavaScript; keyword search uses SQL LIKE (exact phrase first, then per-word fallback). Hybrid mode merges and de-duplicates both result sets. No sqlite-vec, no FTS5 — deliberately simple, and more than adequate at this archive's scale.
A GitHub Actions workflow runs every Tuesday at 09:00 UTC (the morning after the newsletter's usual Monday publish). It incrementally ingests any new issues, verifies the database, and publishes it as a new GitHub Release tagged db-YYYY.MM.DD-NNNN. The NPX server picks up the new database automatically within a week (or immediately on a fresh install). A workflow_dispatch trigger provides a manual escape hatch for off-schedule publishes or full rebuilds.
| OS | Path |
|---|---|
| Windows | %USERPROFILE%\.microsoft-ai-roundup-mcp\ |
| macOS / Linux | ~/.microsoft-ai-roundup-mcp/ |
Delete the folder to force a fresh download of the latest database.
git clone https://github.com/darrenjrobinson/microsoft-ai-roundup-mcp
cd microsoft-ai-roundup-mcp
npm install
npm run build
# Build the search index locally (requires an OpenAI API key for embeddings)
export OPENAI_API_KEY=sk-...
node dist/scripts/ingest.js # full ingest
node dist/scripts/ingest.js --incremental # only new issues
# On Windows there's a PowerShell wrapper:
./scripts/ingest.ps1 -Incremental
# Run the server against your local database
MSAI_ROUNDUP_DB_PATH=./microsoft-ai-roundup.db npx microsoft-ai-roundup-mcp
| Environment variable | Used by | Purpose |
|---|---|---|
OPENAI_API_KEY | ingest + server | Embeddings (required for ingest; optional for the server's semantic search) |
INGEST_DB_PATH | ingest | Output database path (default ./microsoft-ai-roundup.db) |
MSAI_ROUNDUP_DB_PATH | server | Use a local database instead of downloading from GitHub Releases |
Newsletter content is © Merill Fernando & Joshua Fernando. This project indexes the freely available public archive via the public Substack API (all posts are free, audience: "everyone") and always links back to the original issues. The code is MIT licensed.
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