MCP Supabase

Supabase MCP Skill

Interact with Supabase database via MCP tools, execute queries, writes, migrations, and diagnostics.

Scope

Applies to:

• Need to perform "database actions" on Supabase: query/statistics/export, write (after confirmation), migration (DDL), type generation, query logs/advisors

Does not apply to:

• Need to complete "integration implementation" in Next.js project (env/client code/minimal data access layer/project structure)
  → Use workflow-ship-faster (Step 6: Supabase integration) for project-side setup; this skill only handles DB-side actions and gates

Called by:

• workflow-ship-faster uses this skill as DB operation foundation; workflow-ship-faster handles project-side integration, this skill handles DB-side actions and security gates

Postgres Best Practices (Bundled)

Ship Faster vendors Supabase's Postgres best practices inside the supabase skill (install supabase alongside this skill if you want these references available locally):

• Full guide: supabase/references/postgres-best-practices/AGENTS.md
• Individual rules: supabase/references/postgres-best-practices/rules/*.md

Consult it when:

• Writing/reviewing/optimizing SQL queries
• Designing indexes, schema changes, or RLS policies
• Diagnosing performance, locking, or connection issues

When proposing changes, cite the relevant rule file path (for example: supabase/references/postgres-best-practices/rules/query-missing-indexes.md) and keep changes minimal.

File-based Pipeline (Pass Paths Only)

When integrating database operations into multi-step workflows, persist all context and artifacts to disk, passing only paths between agents/sub-agents.

Recommended directory structure (within project): runs/<workflow>/active/<run_id>/

• Input: 01-input/goal.md (requirements), 01-input/context.json (known tables/fields/IDs)
• Plan: 03-plans/sql.md (SQL to execute; write operations must be written here before confirmation)
• Output: 05-final/result.md (conclusion + key numbers + SQL + truncated results)
• Logs: logs/events.jsonl (summary of each tool call; do not log sensitive field values)

Tool Reference

Optional tools (if enabled):

• Edge Functions: list_edge_functions, get_edge_function, deploy_edge_function
• Branching: create_branch, list_branches, merge_branch, reset_branch, rebase_branch, delete_branch

Security Rules (Must Follow)

1. Read first: Always check schema before any operation
2. Default LIMIT 50: All SELECT queries default to LIMIT 50, unless user explicitly requests more
3. Write operation confirmation: INSERT/UPDATE/DELETE must before execution:
   • Display the SQL to be executed
   • State expected number of affected rows
   • Await explicit user confirmation
4. No bare writes: UPDATE/DELETE without WHERE condition → refuse directly, do not execute
5. Batch threshold: Affecting > 100 rows → force double confirmation + suggest SELECT count(*) first
6. DDL via migration: Schema changes must use apply_migration, execute_sql cannot run DDL directly
7. Production environment: Write disabled by default; only allow when user explicitly says "execute on prod" and double confirms
8. Sensitive fields: email/phone/token/password are masked or not returned by default, unless user explicitly requests

Operation Flow

1. Parse requirements → restate objective
2. Unsure about tables/fields → first list_tables or execute_sql to query information_schema
3. Plan SQL → present to user
4. Read-only → execute directly
5. Write operation → confirm before execution → verify affected rows → report result

Output Format

• Language: English
• Structure: Conclusion → Key numbers → Executed SQL → Result table (max 50 rows)
• Overflow handling: Truncate + show total count + optional export/pagination

Example output:

✅ Query complete: 142 new users in the last 7 days

Executed SQL:
SELECT DATE(created_at) as date, COUNT(*) as count 
FROM user_profiles 
WHERE created_at > NOW() - INTERVAL '7 days'
GROUP BY DATE(created_at) ORDER BY date DESC;

| date       | count |
|------------|-------|
| 2025-01-09 | 23    |
| 2025-01-08 | 31    |
| ...        | ...   |

Error Handling

Example Dialogues

Read: Simple Query

User: Get registered user count for the last 7 days, by day
Execution:
1. Confirm table user_profiles, field created_at
2. Execute aggregation SQL
3. Return: conclusion + numbers + SQL + table

Read: Complex Query

User: Find projects that have runs but all failed
Execution:
1. Confirm projects, runs tables and status field
2. Present JOIN + aggregation SQL
3. Execute and return results (mask email)

Write: Insert

User: Create a new run for project xxx
Execution:
1. First check if project exists
2. Present INSERT SQL + expected impact: 1 row
3. Await confirmation → execute → return new record id

Write: Update

User: Change run abc's status to completed
Execution:
1. First SELECT to verify current state
2. Present UPDATE SQL + WHERE id = 'abc'
3. Confirm → execute → SELECT again to verify

Dangerous: Delete

User: Delete all runs where status = 'failed'
Execution:
1. First SELECT count(*) WHERE status = 'failed'
2. Present count + DELETE SQL
3. If > 100 rows, force double confirmation
4. After confirmation execute → report deleted row count

Dangerous: DELETE without WHERE

User: Clear the runs table
Execution:
❌ Refuse to execute
→ Prompt: DELETE without WHERE condition, this will delete all data
→ Suggest: Use TRUNCATE (requires migration) or add explicit condition

Schema Reference

Get latest schema at runtime:

-- List all tables
SELECT table_name FROM information_schema.tables 
WHERE table_schema = 'public';

-- View table structure
SELECT column_name, data_type, is_nullable 
FROM information_schema.columns 
WHERE table_name = '<table_name>';

For project-specific schema (may be outdated), see schema.md. Default to information_schema / generate_typescript_types as source of truth.