Supabase
MCP server for interacting with the Supabase platform
제작자가 쓴 설명(영어 원문)
Read-only MCP for the SQL database behind an ERP: provably read-only guard, public benchmark.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"erp-report-engine": {
"command": "uvx",
"args": [
"erp-report-engine",
"mcp",
"-c",
"your-value"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add erp-report-engine -- uvx erp-report-engine mcp -c your-value이 서버는 실행 명령어에 값을 넣어야 해서, 설정을 복사한 뒤 직접 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"erp-report-engine": {
"command": "uvx",
"args": [
"erp-report-engine",
"mcp",
"-c",
"your-value"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 실행 명령어에 값을 넣어야 해서, 설정을 복사한 뒤 직접 채워 주세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"erp-report-engine": {
"type": "stdio",
"command": "uvx",
"args": [
"erp-report-engine",
"mcp",
"-c",
"your-value"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
레지스트리 이름이 GitHub 계정 gulmezeren2-byte 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.7.0)은 4개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Supabase, MongoDB MCP Server, Elasticsearch MCP Server
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP server for interacting with the Supabase platform
MongoDB Model Context Protocol Server
MCP server for interacting with Elasticsearch
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요