
OCDS German Procurement Search
io.github.qune-techPublished by GitHub account qune-techv0.4.0Updated Oct 24, 2026
Search and match German public procurement tenders (OCDS) from your local LLM.
Overview
Lets an assistant search and match German public procurement tenders (OCDS) using a locally run server and a paid API key.
- What you can do
- Provides eleven tools for German public procurement data: semantic text search over tenders, filtered browsing by phase, CPV prefix, country, value range, deadline, buyer and procurement method, retrieval of raw eForms XML for an OCID, and notice lineage (PIN to CN to CAN). It also manages local company profiles and matches a profile against tenders by semantic similarity. Queries and profile text are embedded locally with a multilingual ONNX model; only vectors, OCIDs, filter values and the API key are sent to the API.
- When to use it
- Use it when an assistant needs to find, filter or track German public tenders, or to check which tenders fit a company profile. It suits users who want query and profile text to stay on their own machine while still using the vendor's search API.
- Requirements
- A local runtime: run via npx with the npm package @qune-tech/ocds-mcp, a pre-built binary, or a Rust build from source. An API key (OCDS_API_KEY, also accepted as VERGABE_API_KEY) from the vendor's dashboard is required and needs an active Pro plan at EUR 99 per month. Internet access to the API, and about 120 MB of disk for the ONNX embedding model downloaded on first run.
Installation
In SourceWeft
- Open OCDS German Procurement Search in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
vergabe-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.
Quick Start
1. Get an API key
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).
2. Install
Via npx (easiest — downloads the correct binary automatically):
Or download a pre-built binary from GitHub Releases:
Linux / macOS:
Windows: Extract the zip and move vergabe-mcp.exe somewhere on your PATH.
Or build from source:
3. Configure your AI client
Claude Desktop — edit claude_desktop_config.json:
Using npx:
Using the binary directly:
Claude Code — add .mcp.json to your project root:
Using npx:
Using the binary directly:
Cursor — Settings → MCP Servers → Add:
Using npx:
- Command:
npx - Args:
-y @qune-tech/vergabe-mcp --api-key sk_live_YOUR_KEY_HERE
Using the binary directly:
- Command:
vergabe-mcp - Args:
--api-key sk_live_YOUR_KEY_HERE
LM Studio — Settings → MCP → Add Server:
- Click + Add Server and choose STDIO
- Fill in:
Using npx:
- Name:
vergabe - Command:
npx - Arguments:
-y @qune-tech/vergabe-mcp --api-key sk_live_YOUR_KEY_HERE
Using the binary directly:
- Name:
vergabe - Command: full path to the binary, e.g.
/usr/local/bin/vergabe-mcp - Arguments:
--api-key sk_live_YOUR_KEY_HERE
- Click Save
- In the chat, select a model that supports tool use and enable the
vergabeserver
LM 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.
Available Tools (11)
CLI Options
How It Works
The MCP server runs locally on your machine:
- Company profiles (name, description, CPV interests, location) are stored in a local SQLite database — they never leave your network.
- Text embeddings are computed locally with a multilingual ONNX model (multilingual-e5-small, 384-dim). Search queries use the
query:prefix and go toPOST /api/v1/search/vector; profile descriptions use thepassage:prefix and go toPOST /api/v1/match/vector. - Only embedding vectors (384 floats), the OCIDs you fetch, filter values, and your API key are sent to the API. Your query and profile text stay local.
Privacy & data flow
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:
- What:
model.onnx+tokenizer.json, ~118 MB total. - When: the first time the embedder runs; cached afterwards at
~/.cache/vergabe/models/multilingual-e5-small. - From:
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.
Requirements
- An API key from vergabe-dashboard.qune.de on the Pro plan (€99/month)
- ~120 MB disk space for the ONNX model (downloaded automatically on first run)
- Internet connection to reach the API
License
MIT — see LICENSE.
Source: README.md at commit fded769
Tools
0Version history
1- v0.4.0LatestSep 16, 2026
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- Auth declared10 pts
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- Tools listed15 pts
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