SIP News

An MCP connector that lets an AI assistant search and read the official news of the Luxembourg government press service (Service information et presse, SIP) at sip.gouvernement.lu.

It exposes the full SIP news archive (press releases, communiqués, speeches, state visits, ministerial news, ~2300 items back to February 2000) as clean, structured, full-text-searchable data, in German, French or English.

Why it exists

The SIP news page loads its list through a JavaScript component, so a naive HTTP fetch returns an empty shell. This connector instead uses the site's own RSS endpoints, which return clean, paginated, newest-first data:

Purpose	Endpoint
Browse all news	GET /{lang}/actualites.rss?page={n}
Full-text search	GET /{lang}/support/recherche.rss?q={query}&page={n}

Each page returns 50 items as a sliding window over the whole archive. The connector pages through automatically, de-duplicates, decodes the (double-encoded) entities, recovers each item's category/language/date from its URL, and can fetch the full article body on demand.

Tools

Tool	What it does
search_news	Keyword full-text search across the whole archive (newest first).
semantic_search	Meaning-based (vector) search; handles natural-language questions.
browse_latest_news	The chronological news feed, newest first.
get_article	Fetch the full, cleaned text of one article by URL.
list_categories	Reference list of category keys and interface languages.
build_semantic_index	(Re)build the local vector index used by semantic_search.
semantic_index_status	Size and coverage of the vector index.

Common parameters:

• language — de, fr or en (interface language; many items are in French regardless, so try more than one if needed).
• limit — how many results to return; larger values page deeper into history.
• since / until — YYYY-MM-DD date bounds.
• category — e.g. communiques (press releases), articles, discours (speeches); see list_categories.

Returned fields per item: title, summary, url, published (ISO), published_human, category, category_label, content_language, source.

search_news / browse_latest_news also return count, complete and an optional note. complete: false means the scan stopped at the page cap or time budget rather than covering the whole archive/range, so a short or empty list there is not an authoritative "nothing exists" (the note explains how to narrow the query). get_article returns the body and a truncated flag.

Semantic search

semantic_search matches news by meaning rather than exact keywords, so it answers natural-language questions ("military cooperation with Belgium", "attacks on state IT systems") even when the wording differs from the article.

How it works:

• build_semantic_index pages through the archive, embeds each item (title + summary) with an embedding model, and stores the vectors in the configured vector store (ChromaDB by default). For NVIDIA retrieval models on OpenRouter, documents are embedded as passage and queries as query (asymmetric retrieval), which sharply improves ranking.
• semantic_search embeds the question and returns the nearest items by cosine similarity, with the same language / category / since / until filters. Each result carries a similarity score in [0, 1].

Setup:

1. Get an OpenRouter API key and put it in the server's environment as OPENROUTER_API_KEY (see the config below). The default model nvidia/llama-nemotron-embed-vl-1b-v2:free is free. (Or use a local embedder instead, see below.)
2. Build the index once (from Claude, call build_semantic_index, or run the one-liner below). A full build covers the whole archive (~2300 items, back to
   2000. in about a minute. Re-run it periodically to pick up new news.

uv run --extra semantic python -c "import asyncio; from sip_news_mcp.semantic import SemanticIndex; print(asyncio.run(SemanticIndex().build(language='fr', max_items=3000)))"

Relevant environment variables:

Variable	Purpose
SIP_NEWS_SEMANTIC	on / off / auto (default auto). Turn semantic search off for a keyword-only server.
OPENROUTER_API_KEY	Embedding API key (only for the default OpenRouter provider).
SIP_NEWS_EMBED_MODEL	Embedding model id (default: the free Nemotron model).
SIP_NEWS_EMBED_BASE_URL	Embedding API base; point at a local server for self-hosted embeddings.
SIP_NEWS_EMBED_API_KEY	Embedding key (falls back to OPENROUTER_API_KEY).
SIP_NEWS_EMBED_INPUT_TYPE	on / off / auto asymmetric retrieval (default auto).
SIP_NEWS_VECTOR_BACKEND	chroma (default) or qdrant.
SIP_NEWS_CHROMA_DIR	Chroma index location; local disk only (default under %LOCALAPPDATA%).

See .env.example.

Local / self-hosted embeddings (Ollama, OpenAI-compatible)

Point SIP_NEWS_EMBED_BASE_URL at any OpenAI-compatible /embeddings server (Ollama, vLLM, LocalAI, text-embeddings-inference, ...). No OpenRouter key is needed. For example, with Ollama (ollama pull nomic-embed-text):

SIP_NEWS_EMBED_BASE_URL=http://localhost:11434/v1
SIP_NEWS_EMBED_MODEL=nomic-embed-text
# no key; input_type is auto-disabled for non-OpenRouter endpoints

Then build the index. (Changing the embedding model/endpoint changes the vector space, so rebuild the index with refresh=true when you switch.)

Keyword-only mode (no RAG, easiest to deploy)

Semantic search is optional. With SIP_NEWS_SEMANTIC=off (or simply by not installing a vector backend), the server exposes only the four keyword tools (search_news, browse_latest_news, get_article, list_categories). No vector database, no embeddings, no OpenRouter key, and none of the heavy optional dependencies are needed, which makes it the simplest thing to deploy.

The vector-DB dependencies are optional extras, so the base install is lightweight:

Install	What you get
pip install .	Keyword-only (no vector deps).
pip install ".[chroma]"	+ embedded ChromaDB backend.
pip install ".[qdrant]"	+ Qdrant backend.
pip install ".[semantic]"	+ both backends.

With SIP_NEWS_SEMANTIC=auto (the default) the server enables semantic search only when the configured backend's library is actually installed.

Requirements

• uv (recommended), or Python 3.10+ with pip.

uv will download a suitable Python automatically; you do not need one installed system-wide.

Note (Windows + network drives). If you keep this project on a network / UNC drive, Python's Windows extensions (pywin32, pulled in by mcp) cannot load their DLLs from a UNC path, so the virtual environment must sit on a local disk. Point UV_PROJECT_ENVIRONMENT at a local folder (the project code can stay on the network drive; only the installed environment needs to be local). The commands and MCP config below set it.

Quick start

cd C:\path\to\SIP-MCP-Connector
$env:UV_PROJECT_ENVIRONMENT = "$env:LOCALAPPDATA\sip-news-mcp\venv"
uv sync --extra semantic --extra dev    # LOCAL env with semantic + test deps
uv run --extra dev pytest               # run the offline test suite
uv run --extra semantic sip-news-mcp    # start the server (stdio, with semantic)
# For a keyword-only server, drop the extras:  uv run sip-news-mcp

A quick live check without an MCP client (run in the same shell, so it reuses the local environment set above):

uv run python -c "import asyncio; from sip_news_mcp.client import SipNewsClient; print(asyncio.run(SipNewsClient().search('cyber', language='de', limit=3)))"

Use it from Claude

Claude Desktop

Add this to claude_desktop_config.json (%APPDATA%\Claude\claude_desktop_config.json on Windows), then restart Claude Desktop. See examples/claude_desktop_config.json:

{
  "mcpServers": {
    "sip-news": {
      "command": "uv",
      "args": ["--directory", "C:\\path\\to\\SIP-MCP-Connector", "run", "--extra", "semantic", "sip-news-mcp"],
      "env": {
        "UV_PROJECT_ENVIRONMENT": "C:\\sip-news-mcp\\venv",
        "OPENROUTER_API_KEY": "sk-or-v1-...your key...",
        "SIP_NEWS_CHROMA_DIR": "C:\\sip-news-mcp\\chroma"
      }
    }
  }
}

(--extra semantic and the OPENROUTER_API_KEY / SIP_NEWS_CHROMA_DIR env are only needed for semantic search; for a keyword-only server drop them. If Claude Desktop cannot find uv, use the absolute path to uv.exe, since it may not inherit your shell PATH.)

Claude Code (CLI)

claude mcp add sip-news `
  --env UV_PROJECT_ENVIRONMENT="$env:LOCALAPPDATA\sip-news-mcp\venv" `
  --env OPENROUTER_API_KEY="sk-or-v1-...your key..." `
  -- uv --directory "C:\path\to\SIP-MCP-Connector" run --extra semantic sip-news-mcp

Example prompts

• "Search SIP for news about cybersécurité in 2025 and summarise the top 5."
• "List all SIP press releases (communiques) since 2026-01-01."
• "Find SIP articles mentioning armée and open the most recent one in full."

Notes and limits

• Search uses the SIP site's own full-text engine, which is a broad match: a hit may mention the term only in its body, and ranking is the site's, not ours. The connector returns those results faithfully. Use get_article to confirm relevance before quoting.
• Content language varies per item; the connector reports content_language per result so you can tell French items from German ones.
• Date filtering is most efficient for recent ranges (the feed is newest-first and stops early once it passes since); very old ranges page deeper and may hit the page cap or the ~45s time budget, in which case the result is marked complete: false with an explanatory note.
• Identical requests are cached in-process for 5 minutes (bounded LRU), so repeating the same query does not re-hit the server. A single search/browse call still issues up to ~40 sequential page requests, but they are made one at a time (each awaited before the next) under a descriptive User-Agent, which keeps load on the public government server modest.
• get_article only fetches https URLs on sip.gouvernement.lu (host is parsed and checked, not substring-matched), so it cannot be turned into a request to other hosts.
• This connector only reads public pages; it performs no writes and needs no credentials.

Deployment (Docker / Kubernetes)

The server speaks two transports, chosen by MCP_TRANSPORT:

• stdio (default) for Claude Desktop / Code (local subprocess).
• http (streamable-http) for containers and Kubernetes, listening on MCP_HOST:MCP_PORT (default 0.0.0.0:8000, path /mcp).

It also supports two vector backends via SIP_NEWS_VECTOR_BACKEND:

• chroma (embedded, default) for local use.
• qdrant (a shared, network Qdrant) for containers / multiple replicas, set with QDRANT_URL (and optional QDRANT_API_KEY).

Docker Compose

Brings up Qdrant + the MCP server (HTTP) together:

echo "OPENROUTER_API_KEY=sk-or-v1-...your key..." > .env
docker compose up -d --build
docker compose run --rm index-build      # populate the vector index once
# MCP server: http://localhost:8000/mcp   (streamable-http)

Minimal / keyword-only (no RAG)

The simplest deployment: no Qdrant, no embeddings, no API key. Just the four keyword tools.

docker compose -f docker-compose.minimal.yml up -d --build
# MCP server on http://localhost:8000/mcp

The minimal image is built with no vector-DB dependencies (docker build --build-arg EXTRAS="" -t sip-news-mcp:minimal .) and runs with SIP_NEWS_SEMANTIC=off.

Docker (image only)

docker build -t sip-news-mcp:latest .                 # full (RAG) image
docker run --rm -p 8000:8000 \
  -e OPENROUTER_API_KEY=sk-or-v1-... \
  -e SIP_NEWS_VECTOR_BACKEND=qdrant -e QDRANT_URL=http://host.docker.internal:6333 \
  sip-news-mcp:latest

Kubernetes (Helm)

The chart in deploy/helm/sip-news-mcp deploys the server, a bundled Qdrant (StatefulSet + PVC), a Secret for the API key, and an optional one-shot Job that builds the index after install.

helm install sip-news deploy/helm/sip-news-mcp \
  --set openrouter.apiKey=sk-or-v1-...your key...
# or reference an existing Secret:  --set openrouter.existingSecret=my-secret

For a keyword-only deployment (just a Deployment + Service, no Qdrant, Secret or Job), set semantic.enabled=false:

helm install sip-news deploy/helm/sip-news-mcp --set semantic.enabled=false

Key values (see values.yaml):

Value	Default	Purpose
semantic.enabled	true	Set false for a keyword-only server (no Qdrant/key/Job).
vector.backend	qdrant	qdrant or chroma.
qdrant.enabled	true	Deploy a bundled Qdrant; set false + qdrant.url for an external one.
openrouter.apiKey	""	API key (creates a Secret), or use existingSecret.
indexBuild.enabled	true	Run a post-install Job to populate the index (qdrant backend).
ingress.enabled	false	Expose via an Ingress.
replicaCount	1	Scale out (qdrant backend; keep 1 for chroma).

Reach it with kubectl port-forward svc/sip-news-... 8000:8000, then point an MCP client at http://localhost:8000/mcp.

Connecting an MCP client over HTTP

Claude Desktop's config is stdio-only; to use the HTTP server, configure an MCP client that supports the streamable-http transport with URL http://<host>:8000/mcp.

Project layout

src/sip_news_mcp/
  client.py       HTTP client, RSS/article parsers, filtering, pagination
  semantic.py     OpenRouter embeddings + the SemanticIndex
  vectorstore.py  pluggable vector backends (ChromaDB / Qdrant)
  build_index.py  `sip-news-index` CLI (one-shot index build, used by jobs)
  server.py       FastMCP server, tool definitions, stdio/http transport
  __main__.py     `python -m sip_news_mcp`
tests/
  test_urls.py          URL / host / selector-metadata tests
  test_parsing.py       RSS feed + article parser tests
  test_client.py        SipNewsClient pagination / filtering tests
  test_semantic.py      vector layer tests (fake embedder)
  test_server_config.py semantic on/off/auto config logic
  test_server_tools.py  MCP tool registration / integration (each tool >=2x)
  conftest.py           shared fixtures; fixtures/ captured live responses
Dockerfile          container image (HTTP transport)
docker-compose.yml  Qdrant + MCP server + one-shot index build
deploy/helm/sip-news-mcp/   Kubernetes Helm chart
examples/
  claude_desktop_config.json