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

AI-generated 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.
Before you install
The API key is a live secret passed on the command line or by environment variable; keep it out of shared config files. The Pro plan costs EUR 99 per month. The API receives embedding vectors, the OCIDs read, filter values and the key, which reveal commercial interest even though query and profile text stay local. Profiles are stored in a local SQLite database and can be created, updated and deleted. The first run downloads the embedding model from a third-party host.

Installation

In SourceWeft

  1. Open OCDS German Procurement Search in the dashboard and add it to a workspace.
  2. 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):

bash
npx @qune-tech/vergabe-mcp --api-key sk_live_YOUR_KEY_HERE

Or download a pre-built binary from GitHub Releases:

PlatformDownload
Linux x86_64vergabe-mcp-linux-x86_64.tar.gz
macOS Apple Siliconvergabe-mcp-macos-arm64.tar.gz
Windows x86_64vergabe-mcp-windows-x86_64.zip

Linux / macOS:

bash
# Example for Linux x86_64 — adjust the filename for your platformtar xzf vergabe-mcp-linux-x86_64.tar.gzsudo 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:

bash
git clone https://github.com/qune-tech/vergabe-mcp.gitcd vergabe-mcpcargo build --release# Binary at target/release/vergabe-mcp

3. Configure your AI client

Claude Desktop — edit claude_desktop_config.json:

Using npx:

json
{  "mcpServers": {    "vergabe": {      "command": "npx",      "args": ["-y", "@qune-tech/vergabe-mcp", "--api-key", "sk_live_YOUR_KEY_HERE"]    }  }}

Using the binary directly:

json
{  "mcpServers": {    "vergabe": {      "command": "vergabe-mcp",      "args": ["--api-key", "sk_live_YOUR_KEY_HERE"]    }  }}

Claude Code — add .mcp.json to your project root:

Using npx:

json
{  "mcpServers": {    "vergabe": {      "command": "npx",      "args": ["-y", "@qune-tech/vergabe-mcp", "--api-key", "sk_live_YOUR_KEY_HERE"]    }  }}

Using the binary directly:

json
{  "mcpServers": {    "vergabe": {      "command": "vergabe-mcp",      "args": ["--api-key", "sk_live_YOUR_KEY_HERE"]    }  }}

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:

  1. Click + Add Server and choose STDIO
  2. 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
  1. Click Save
  2. In the chat, select a model that supports tool use and enable the vergabe server

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)

ToolDescription
search_textSemantic search across all tenders (query embedded locally)
list_releasesFilter and browse tenders by phase, CPV prefix, country, value range, deadline, buyer, procurement method
get_releaseRaw eForms XML envelope for one OCID (optional notice_id selects a sibling)
linked_noticesA procurement's notice lineage (PIN→CN→CAN) as {ocid, notice_id} refs
get_index_infoAPI health/version, embedder status, and embedding-contract check
create_company_profileCreate a matching profile for your company (stored locally)
update_company_profileUpdate an existing profile
get_company_profileView profile details
list_company_profilesList all your profiles
delete_company_profileDelete a profile
match_tendersMatch a profile against all tenders by semantic similarity (vector embedded locally)

CLI Options

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

How It Works

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:

  • 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 to POST /api/v1/search/vector; profile descriptions use the passage: prefix and go to POST /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

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.4.0LatestSep 16, 2026

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