building_enrich
Enrich a location with European building intelligence: roof surfaces (m²), parking areas, solar-obligation status under French loi APER and loi Climat-Résilience, existing solar installations. Covers 628,000 scanned roofs and 91,800 parkings across 6 EU countries (FR, DE, IT, ES, BE, NL). Determi...
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/building-enrich.md
What building_enrich does on Mcp Knowledge
AI agents call building_enrich to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
lat | number | Yes | Latitude (WGS84) |
lng | number | Yes | Longitude (WGS84) |
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
radiusM | integer | — | Search radius in metres (default 150, max 500) |
minAreaM2 | integer | — | Only return roofs/parkings at least this large, in m² |
Parameters from the server's own tool schema.
Why building_enrich is rated Low
Tool queries existing building data with no creation, modification, deletion, or execution capability.
From the tool's definition Enrich location with building intelligence: roof surfaces, parking areas, solar-obligation status. Deterministic database lookup.
Attacks that exploit this kind of access
The rule that runs building_enrich safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For building_enrich, this is the rule to start with:
building_enrich is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every building_enrich call is checked against it from then on.
Questions about building_enrich
Enrich a location with European building intelligence: roof surfaces (m²), parking areas, solar-obligation status under French loi APER and loi Climat-Résilience, existing solar installations. Covers 628,000 scanned roofs and 91,800 parkings across 6 EU countries (FR, DE, IT, ES, BE, NL). Deterministic database lookup — no LLM, no generation, sub-second. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.
building_enrich accepts 5 parameters: lat, lng, async, radiusM, minAreaM2. Required: lat, lng. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for building_enrich: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp Knowledge. Nothing to install.
building_enrich is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the building_enrich rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for building_enrich. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
building_enrich is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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