Deprecated. Deprecated by the publisher: Renamed to @qune-tech/vergabe-mcp - this package speaks a retired API and no longer works. Install @qune-tech/vergabe-mcp instead.
Search and match German public procurement tenders (OCDS) from your local LLM.
Runs on your machine from its package; the steps are below.
At most: only reads or looks up information.
Odel charges nothing per call. The publisher may charge for its own service.
Runs locally over stdio
This server isn't hosted — your MCP client launches it from a package registry. Use one of the commands below, or drop the config into your client (e.g. Claude Desktop).
Run
npx -y @qune-tech/ocds-mcp
MCP client config
{
"mcpServers": {
"ocds-german-procurement-search": {
"command": "npx",
"args": [
"-y",
"@qune-tech/ocds-mcp"
]
}
}
}Local MCP server for German public procurement search. Connects your AI assistant (Claude, GPT, etc.) to the Vergabe Dashboard API for semantic search, tender matching, and company-profile management.
Your queries and company profiles never leave your machine. They are embedded locally with a multilingual ONNX model; only the resulting embedding vectors, OCIDs, and filter values are sent to the API. Data minimisation by design.
Hosted alternative: if you just want search from your AI assistant, there is a hosted MCP connector (OAuth sign-in, no installation) — see the setup guide. This local server is for running the client in your own environment: queries and profiles are embedded locally, only vectors and filter values leave the machine, and it unlocks API-key features.
New to German public procurement? The Vergabe Dashboard knowledge base explains eForms, EU thresholds, and the tender lifecycle, and KI für Vergabe covers the hosted AI side of this server.
Sign up at vergabe-dashboard.qune.de and create an API key. API keys require an active Pro plan (€99/month; the local server itself is free and open source — the API gate rides key issuance).
Via npx (easiest — downloads the correct binary automatically):
npx @qune-tech/vergabe-mcp --api-key sk_live_YOUR_KEY_HERE
Or download a pre-built binary from GitHub Releases:
| Platform | Download |
|---|---|
| Linux x86_64 | vergabe-mcp-linux-x86_64.tar.gz |
| macOS Apple Silicon | vergabe-mcp-macos-arm64.tar.gz |
| Windows x86_64 | vergabe-mcp-windows-x86_64.zip |
Linux / macOS:
# Example for Linux x86_64 — adjust the filename for your platform
tar xzf vergabe-mcp-linux-x86_64.tar.gz
sudo mv vergabe-mcp /usr/local/bin/vergabe-mcp
Windows: Extract the zip and move vergabe-mcp.exe somewhere on your PATH.
Or build from source:
git clone https://github.com/qune-tech/vergabe-mcp.git
cd vergabe-mcp
cargo build --release
# Binary at target/release/vergabe-mcp
Claude Desktop — edit claude_desktop_config.json:
Using npx:
{
"mcpServers": {
"vergabe": {
"command": "npx",
"args": ["-y", "@qune-tech/vergabe-mcp", "--api-key", "sk_live_YOUR_KEY_HERE"]
}
}
}
Using the binary directly:
{
"mcpServers": {
"vergabe": {
"command": "vergabe-mcp",
"args": ["--api-key", "sk_live_YOUR_KEY_HERE"]
}
}
}
Claude Code — add .mcp.json to your project root:
Using npx:
{
"mcpServers": {
"vergabe": {
"command": "npx",
"args": ["-y", "@qune-tech/vergabe-mcp", "--api-key", "sk_live_YOUR_KEY_HERE"]
}
}
}
Using the binary directly:
{
"mcpServers": {
"vergabe": {
"command": "vergabe-mcp",
"args": ["--api-key", "sk_live_YOUR_KEY_HERE"]
}
}
}
Cursor — Settings → MCP Servers → Add:
Using npx:
npx-y @qune-tech/vergabe-mcp --api-key sk_live_YOUR_KEY_HEREUsing the binary directly:
vergabe-mcp--api-key sk_live_YOUR_KEY_HERELM Studio — Settings → MCP → Add Server:
Using npx:
vergabenpx-y @qune-tech/vergabe-mcp --api-key sk_live_YOUR_KEY_HEREUsing the binary directly:
vergabe/usr/local/bin/vergabe-mcp--api-key sk_live_YOUR_KEY_HEREvergabe serverLM Studio requires models with tool-calling support (e.g. Qwen 2.5, Mistral, Llama 3.1+). Smaller models may not use all 11 tools reliably — 7B+ recommended.
Replace sk_live_YOUR_KEY_HERE with your actual API key. You can also pass the key via the VERGABE_API_KEY environment variable.
| Tool | Description |
|---|---|
search_text | Semantic search across all tenders (query embedded locally) |
list_releases | Filter and browse tenders by phase, CPV prefix, country, value range, deadline, buyer, procurement method |
get_release | Raw eForms XML envelope for one OCID (optional notice_id selects a sibling) |
linked_notices | A procurement's notice lineage (PIN→CN→CAN) as {ocid, notice_id} refs |
get_index_info | API health/version, embedder status, and embedding-contract check |
create_company_profile | Create a matching profile for your company (stored locally) |
update_company_profile | Update an existing profile |
get_company_profile | View profile details |
list_company_profiles | List all your profiles |
delete_company_profile | Delete a profile |
match_tenders | Match a profile against all tenders by semantic similarity (vector embedded locally) |
Usage: vergabe-mcp [OPTIONS]
Options:
--db <DB> Local profiles database [default: profiles.db]
--data-dir <DIR> Data directory [default: data]
--api-url <URL> Vergabe Dashboard API [default: https://vergabe-dashboard.qune.de]
--api-key <KEY> API key [env: VERGABE_API_KEY]
-h, --help Print help
LLM ←stdio→ vergabe-mcp (local)
│ Local: company profiles (SQLite) + sentence embedder (ONNX)
│ HTTPS: vectors, OCIDs, filter values, API key
└──HTTPS──→ Vergabe Dashboard API (/api/v1)
The MCP server runs locally on your machine:
query: prefix and go to POST /api/v1/search/vector; profile descriptions use the passage: prefix and go to POST /api/v1/match/vector.What stays on your machine: profile text, search-query text, CPV interests, location.
What the API sees: embedding vectors, the OCIDs you read, the filter values you use, and your API key. These reveal commercial interest (which sectors, buyers, value bands, tenders you look at) but not the underlying text. Embedding vectors are a derived, pseudonymous representation — minimisation, not elimination.
First-run model download: on first use the server downloads the embedding model from huggingface.co:
model.onnx + tokenizer.json, ~118 MB total.~/.cache/vergabe/models/multilingual-e5-small.huggingface.co (a US-operated third party). No user data is sent in this fetch — it is a plain model download.For air-gapped / enterprise installs, place model.onnx and tokenizer.json in the cache directory above and the runtime download is skipped.
MIT — see LICENSE.