Supabase
MCP server for interacting with the Supabase platform
Descripción del creador (original en inglés)
Read-only MCP for the SQL database behind an ERP: provably read-only guard, public benchmark.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"erp-report-engine": {
"command": "uvx",
"args": [
"erp-report-engine",
"mcp",
"-c",
"your-value"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add erp-report-engine -- uvx erp-report-engine mcp -c your-valueEste necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"erp-report-engine": {
"command": "uvx",
"args": [
"erp-report-engine",
"mcp",
"-c",
"your-value"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"erp-report-engine": {
"type": "stdio",
"command": "uvx",
"args": [
"erp-report-engine",
"mcp",
"-c",
"your-value"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 8 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub gulmezeren2-byte, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.7.0) llegó al registro hace 4 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Supabase, MongoDB MCP Server, Elasticsearch MCP Server
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
MCP server for interacting with the Supabase platform
MongoDB Model Context Protocol Server
MCP server for interacting with Elasticsearch
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
The numbers for Monday's meeting are already sitting in your ERP's database. So who's still writing the report?
**A read-only, self-verifying data layer for the SQL database behind your ERP — weekly reports *and* a guarded MCP server for AI agents. Every query provably read-only: measured against 28 attacks, not promised in prose.**
🇹🇷 Türkçesi: README.tr.md
One scheduled run executes 9 audited SELECT statements and delivers a self-contained HTML report: four KPIs against an 8-week baseline, findings with named drivers, a data-quality gate, and row counts reconciled against the source. No BI license, no agent installed on the ERP server, and no writes — enforced in four layers (lexical, parse-tree, a side-effecting-function guard, and a read-only session), not promised in prose.
*This exact report was produced by one command against the bundled demo database — including the three data-quality problems deliberately seeded into it, all caught by the gate.*
The same guarded engine talks to AI agents, too. erp-report-engine mcp exposes the ERP to an agent through *canonical entities* (orders, never LG_001_01_ORFICHE) behind the same read-only guard — the layer the MCP ecosystem keeps getting wrong. The reference PostgreSQL MCP server's read-only mode was walked out of with COMMIT; DROP SCHEMA public CASCADE; and archived; Supabase's MCP became the textbook "lethal trifecta". Here the guard checks the functions a statement calls, not just its shape — and you don't have to take the adjective's word for it:
▶ [Run the 28-attack trust benchmark](https://gulmezeren2-byte.github.io/erp-report-engine/trust.html) · [break the guard yourself, in your browser](https://gulmezeren2-byte.github.io/erp-report-engine/playground.html) (the real guard.py, via Pyodide, nothing sent anywhere).
*The exact guard.py the tests run, executing in the browser — a file read and the read-only-transaction escape refused, a real aggregate allowed. Paste your own attack →*
# install (pipx or uv keep it isolated; plain pip works too)
pipx install erp-report-engine # or: uv tool install erp-report-engine
erp-report-engine init-demo # builds demo.db + config.demo.yaml here erp-report-engine run -c config.demo.yaml
Every command is also available as python -m erp_report_engine …. Add a database driver with the extras: pipx install "erp-report-engine[mssql]" (Logo Tiger / Netsis / Mikro — SQL Server) or [postgres].
Prefer Docker? docker build -t erp-report-engine . then docker run --rm -v "$PWD:/work" erp-report-engine run -c config.demo.yaml. SQLite and PostgreSQL work out of the box; for MSSQL add Microsoft's ODBC driver (see the Dockerfile). Publishing to PyPI is a GitHub Release away — publish.yml builds and uploads via Trusted Publishing (OIDC, no stored token), and CI already builds the wheel and asserts every bundled profile ships.
Open reports/erp_report_ .html. You'll see the engine catch a revenue spike and attribute it to one region, flag a two-point on-time decline, list items below two weeks of stock cover — and confess every duplicate and negative row it found on the way.
▶ See a live sample report: [gulmezeren2-byte.github.io/erp-report-engine](https://gulmezeren2-byte.github.io/erp-report-engine/) (also committed at docs/sample-report.html).
Or run run --dashboard for the premium Command Center — a dark, modern, self-contained dashboard with animated KPIs and glowing SPC control-band charts ([live](https://gulmezeren2-byte.github.io/erp-report-engine/dashboard.html)):
| Section | What it answers |
|---|---|
| KPI cards | Revenue, orders, on-time %, low-stock count — each vs last week and vs an 8-week baseline |
| Findings | *"Revenue +6.5% week-over-week — main driver: region 'Ege' (54% of the week's movement, partly offset by Marmara (−14,697))"* — driver named, the segment pulling the other way named too, action suggested |
| Signals (SPC) | *"Revenue signal: 148,291 is ABOVE the control limits (UCL 143,078 = mean 93,168 ± 2.66 × avg moving range 18,763, baseline n=25 weeks)"* — a genuine shift, separated from week-to-week noise, with the arithmetic and its sample size shown |
| Trends | 13 full weeks of revenue and on-time %, inline SVG (no external assets) |
| Stock attention list | Items below the cover threshold, worst first |
| Data-quality gate | Duplicate IDs, unparseable dates, negative totals, ship-before-order rows |
| Source reconciliation | Rows fetched vs an independent COUNT(*) of the same query — ✓ or MISMATCH |
| SQL audit trail | Every statement executed, with parameters, row counts and timings |
| Run-state memory | *"Revenue has declined 3 consecutive weeks"* — context beyond the lookback window |
flowchart LR
DB[("ERP database MSSQL · PostgreSQL · SQLite")] PROF["Semantic profile (YAML contract)"] GUARD["safe_read read-only guard + audit"] GATE["Data-quality gate
ISO weeks, 8-wk baseline"] INS["Insight rules driver attribution"] HTML["Self-contained HTML report"] STATE[("state.db run memory")]
PROF --> GUARD DB --> GUARD --> GATE --> KPI --> INS --> HTML STATE --- HTML GATE --> PBI["Power BI Command Center (TMDL + PBIR, code-authored)"]
The layer that makes this portable is the semantic profile: a versioned YAML contract that maps one ERP's cryptic schema to three canonical entities — orders, order_lines, inventory — plus an optional `receivables` entity (open AR, for aging) that a profile maps when the ledger is reachable and everything downstream skips gracefully when it isn't. The engine only ever sees canonical columns. Swap the profile, keep the report.
Pointing software at a production ERP database is a trust decision. This engine treats it that way — the guarantees are enforced in code and covered by tests:
Read-only is enforced in four layers, so no single mistake makes the engine capable of writing:
| Layer | Enforced by |
|---|---|
| Lexical guard | Single statement, SELECT/WITH head, no comments (--, /*, #), no write/DDL keyword, no write-escalating lock hint (TABLOCKX, UPDLOCK, XLOCK). Scanned with string literals blanked, so SELECT 'please delete this note' is a read, not a threat |
| Parse-tree guard | sqlglot parses the statement — and must succeed, or the query is refused: a guard that can't read a query can't vouch for it. It must be a single read query whose AST holds no INSERT/UPDATE/DELETE/CREATE/DROP/ALTER/MERGE/EXEC/INTO node (catches writes hidden inside CTEs) |
| Function guard | Plenty of pure-looking `SELECT`s are not reads. pg_read_file, lo_export (which *writes* a file), dblink (which dials out), OPENROWSET, LOAD_FILE, load_extension (arbitrary code), query_to_xml (arbitrary SQL), set_config (switches off the session backstop), SLEEP/BENCHMARK (denial of service) — all refused, by AST and lexically, because OPENROWSET is precisely what sqlglot cannot parse |
| Read-only session | PostgreSQL default_transaction_read_only=on, SQLite PRAGMA query_only, MySQL SET SESSION TRANSACTION READ ONLY + max_execution_time, and a per-statement timeout everywhere |
Ad-hoc SQL — the agent path — is stricter still. query and guarded_query run in strict mode, which default-denies *every function the guard cannot name*: sqlglot's function registry is the allowlist, since it knows the portable analytic functions and nothing that reads a file or opens a socket. All four bundled profiles pass it — they call no unrecognised function at all.
And the layer that isn't ours. MSSQL has no session-level read-only switch, so run the engine under a least-privilege, read-only login (db_datareader on MSSQL, a SELECT-only grant on PostgreSQL — ideally a read replica). The guard is defence in depth; the grant is the layer that holds if the guard has a hole. It has had one before: these function bypasses were found by auditing this repo, and are now pinned in tests/test_guard.py by name, per dialect.
Don't take my word for it — measure it. The guard ships with a reproducible trust benchmark: 28 well-formed-SQL attacks across four dialects that a shape-only guard waves through, every one refused, plus the legitimate reads that must still pass. The number is computed from a live guard run, not asserted in prose, and CI enforces it on every commit.
And "28/28" only means something next to what a weaker guard scores on the *same* 28. So the benchmark runs the corpus through the shortcuts real tools actually ship — a starts-with-SELECT head check and a write-keyword blocklist — and shows the gap: they refuse 6 and 9 of the 28, and the keyword scan even blocks a legitimate read whose text contains the word "delete", while this guard refuses all 28 and blocks none. A test pins that it strictly beats every such shortcut.
erp-report-engine trust-benchmark
▶ See the results: [the trust benchmark](https://gulmezeren2-byte.github.io/erp-report-engine/trust.html) — every case, its severity, and what it actually does. Or [break it yourself](https://gulmezeren2-byte.github.io/erp-report-engine/playground.html): paste SQL into the real guard, running in your browser (no install, nothing sent anywhere — it's the exact guard.py the tests run, via Pyodide).
Want just the guard for your *own* MCP server or DB
Solo se muestra el principio; lee el resto en el repo