Applies a migration to the database. Use this when executing DDL operations. Do not hardcode references to generated IDs in data migrations.
Bulk support: accepts project_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| query | Yes | ||
| project_id | Yes | ||
| project_ids | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations declare destructiveHint=false, but the description states the tool can execute DDL operations, which often include destructive actions like DROP or ALTER. This contradicts the non-destructive hint. Additionally, the description adds no further behavioral context beyond the warning about hardcoded IDs and bulk support, which are not enough to compensate for the contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely compact yet packs in purpose, usage guidance, a caution, and bulk-support callout. Every sentence earns its place without redundancy, and the information is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description does not explain return values, idempotency, error behavior, or the meaning of required parameters. It also does not mention that migrations may have side effects (destructive or irreversible). For a mutation tool, this leaves significant gaps in understanding the full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only partially explains parameters. It mentions that 'project_ids' enable bulk execution, which adds some meaning, but 'name', 'query', and 'project_id' remain unexplained. Without elaboration, the agent cannot fully understand what values to provide, especially for 'name' and 'query'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Applies a migration to the database.' It uses a specific verb ('Applies') and resource ('migration'), and also provides context by mentioning 'DDL operations.' However, it does not explicitly differentiate from sibling tools like supabase_execute_sql, which could also execute DDL queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives an explicit when-to-use directive: 'Use this when executing DDL operations.' It also adds a guardrail for data migrations and mentions bulk support. However, it does not explicitly state when to avoid this tool or name alternative tools, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The Supabase-prefixed tools are all distinct CRUD/lifecycle operations on different resource types (projects, branches, migrations, edge functions, etc.). The platform-level tools (authenticate, connect, marketplace, etc.) have clear non-overlapping purposes, though their names could momentarily be confused with Supabase-specific actions if an agent doesn't read descriptions.
The 29 supabase_* tools follow a consistent 'supabase_<verb>_<noun>' pattern. However, the 6 non-prefixed platform tools (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) break this convention and are inconsistent among themselves, creating a mixed naming style across the set.
At 35 tools, the server is overweight. While the Supabase domain is broad (project management, database, edge functions, branches), the inclusion of 6 unrelated platform tools inflates the count. 29 domain tools still exceeds the comfortable 15-tool upper bound, making the surface feel bloated for agents to navigate.
The tool set covers core workflows: project lifecycle (create, get, list, pause, restore), branching (create, delete, list, merge, rebase, reset), SQL/migrations, edge functions, cost estimation, and advisors. However, there are notable gaps such as no delete_project, no update operations for projects or branches, and no deletion for edge functions, which leave lifecycle coverage incomplete.