Server data from the Official MCP Registry
Audit a data file before publishing: one light per figure. Your data never reaches the server.
About
Audit a data file before publishing: one light per figure. Your data never reaches the server.
Remote endpoints: streamable-http: https://arquestra.dev/api/mcp/audit
Security Report
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
5 tools verified · Open access · No issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Found in Source Code
Found by scanning the linked source code. This listing connects to a hosted endpoint, so none of this runs on your machine: it describes what the server software does where it is hosted.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-pablo-ramossanchez-arquestra-audit": {
"url": "https://arquestra.dev/api/mcp/audit"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Arquestra Audit · MCP server
Check your own data before you publish a result from it. Arquestra Audit is a remote MCP server by Arquestra that walks your AI assistant through an audit of a data file: it agrees with you how to read each column, measures the file where it is (in the chat's audit panel or with a small script on your computer), and shows one light per figure, red, amber or green, with the reasons.
Your data never reaches the server and nothing is stored. The measuring runs in your browser or on your computer; only counts come back.
- Endpoint:
https://arquestra.dev/api/mcp/audit(Streamable HTTP, no sign-in) - Page: arquestra.dev/assets/audit
Connect it
Claude (claude.ai, desktop, mobile): open Claude's connectors, search Arquestra Audit and press Connect. Not in the list yet? Add it directly.
Claude Code:
claude mcp add --transport http arquestra-audit https://arquestra.dev/api/mcp/audit
or install this repository as a plugin (Manage plugins → Install by GitHub URL → https://github.com/pablo-ramossanchez/arquestra-audit-mcp).
VS Code: install
Cursor: install
ChatGPT: settings → connectors (developer mode) → add https://arquestra.dev/api/mcp/audit.
Any other MCP client: add a remote server with the URL above.
Tools
| Tool | What it does |
|---|---|
start_audit | Proposes how to read your file (the role of each column, each result written as a claim) from its column names and the results you want to publish. |
measure_in_app | Opens the audit panel in the chat; the panel reads your file in your browser and measures it with the confirmed reading. |
prepare_script | Returns measure.py, a fixed Python script (standard library, no network) that counts what each check needs and prints counts, never rows. |
show_audit | Shows the lights: one per figure, with the reasons and a small chart. |
example_audits | How the audit works, with worked examples. |
About Arquestra
Arquestra builds open, checkable data assets on public procurement and AI governance: the Consulting Market Radar (public consulting tenders in Europe and who wins them), the AI Procurement Observatory, research papers, and this audit.
Earlier versions of this repository held a plugin for a scientific-computing product; that product is now listed as Arquestra Chem on arquestra.dev.
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