Boamp MCP Server

The Boamp Server is a dedicated MCP (Model Context Protocol) endpoint that exposes the French public procurement database (BOAMP) to AI assistants. By turning BOAMP’s RESTful API into a lightweight, language‑agnostic service, the server lets Claude or other AI tools perform complex market‑research queries without leaving their native interface. Developers can now embed public‑tender search and detail retrieval directly into conversational agents, dashboards, or automated workflows.

At its core, the server offers two intuitive tools: get_public_markets and get_market_details.

• get_public_markets pulls a list of public‑market notices based on keywords, market type (services, works, supplies), geographic department codes, and pagination limits. The tool also supports sorting by publication or deadline dates, making it easy to surface the most relevant opportunities.
• get_market_details returns a full record for a single tender identified by its unique . This includes contract value, deadlines, and all metadata that the BOAMP API provides.

These capabilities translate into practical use cases such as:

• Targeted opportunity scouting – a sales team can ask an AI assistant to “find digital communication tenders in Île‑de France” and receive a curated list instantly.
• Automated reporting – an internal bot can fetch new tenders weekly, export them to CSV or a database, and trigger alerts when deadlines approach.
• Compliance monitoring – auditors can query all works tenders in a region and cross‑check awarded contracts against internal budgets.

Integration is straightforward: once the server is registered in Claude Desktop’s configuration, any prompt that includes a call to or will be routed through the MCP protocol, returning JSON that the assistant can parse and display. Because the server runs locally or on a private network, sensitive procurement data never leaves the organization’s perimeter.

What sets Boamp Server apart is its focus on a single, high‑value public data source and the ease of extending it to other contexts. Developers can quickly add new filtering parameters or combine the results with external datasets (e.g., budget limits, supplier ratings) to create a fully automated procurement intelligence pipeline—all powered by the same MCP framework that underpins modern AI assistants.