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## I have read the [CONTRIBUTING.md](<https://github.com/supabase/supabase/blob/master/CONTRIBUTING.md>) file. YES ## What kind of change does this PR introduce? Feature / refactor. ## What is the current behavior? The dashboard assistant runs `@supabase/mcp-server-supabase` in-process over an in-memory transport (`lib/ai/supabase-mcp.ts`). ## What is the new behavior? The assistant connects to the **remote MCP server** over HTTP (`@ai-sdk/mcp`), forwarding the dashboard session token as a bearer. URL comes from `NEXT_PUBLIC_MCP_URL` with a local-dev fallback; platform-only, and Nimbus works via the same env var. * **Tool model unchanged:** UI-controlled `execute_sql` (with `needsApproval`) and `deploy_edge_function` still come from Studio; the allowlist (`TOOL_CATEGORY_MAP`) remains the gate keeping the remote's write tools away from the assistant (`read_only` is defense-in-depth). * **Attribution:** sends `x-source-name: supabase-studio` (+ `x-source-version`) → logged as `source_name`/`client_name`. * **Connection lifecycle:** the HTTP client is closed via the request's `AbortSignal` (tools execute later during streaming); `signal` is required on `getTools`/`getMcpTools`. * **Resilience:** a remote-MCP failure degrades to the remaining tools instead of failing the assistant. * **Drift protection:** relied-upon tools are typed against `keyof typeof supabaseMcpToolSchemas`, so a package bump that renames/removes one fails `pnpm typecheck`; a runtime check also warns if the deployed server returns fewer tools. * Adds unit tests for the above. ## Additional context * Verified end-to-end against a local remote MCP server with a dashboard token: `initialize` 200, tools listed, a tool executed, client closed cleanly. * The remote MCP (mgmt-api) already accepts dashboard session tokens (GoTrue-JWT auth path) — no backend change needed. `NEXT_PUBLIC_MCP_URL` must point at each env's `/mcp`. * `@supabase/mcp-server-supabase` is kept — still used by the self-hosted `/api/mcp` routes. Closes [AI-137](https://linear.app/supabase/issue/AI-137/switch-dashboard-assistant-to-remote-mcp) ## Rollout * **Rollout:** merges with `USE_REMOTE_MCP` off (in-process); flip it to `true` per environment (staging → prod → Nimbus) once each one's prerequisites land. * **Rollback:** unset `USE_REMOTE_MCP` and redeploy to fall back to the in-process client — no revert needed. ## Summary by CodeRabbit * **Bug Fixes** * Improved AI request handling so tool loading and generation clean up properly when a request is cancelled or the browser connection closes. * Added safer fallback behavior when remote tool loading fails, so AI features can continue with available tools instead of stopping entirely. * Updated remote tool access to use the current project reference and preserve the correct access headers. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * AI tools now connect more reliably to remote services and stop cleanly when requests end or are canceled. * Tool loading is more resilient, continuing with available tools if remote access is unavailable. * **Bug Fixes** * Improved cleanup to prevent lingering connections during SQL generation and policy workflows. * Added safer handling for remote tool changes and invalid responses. * **Tests** * Expanded automated coverage for remote tool setup, cancellation, and fallback behavior. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
181 lines
6.4 KiB
TypeScript
181 lines
6.4 KiB
TypeScript
import { generateText, Output, stepCountIs } from 'ai'
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import { IS_PLATFORM } from 'common'
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import { source } from 'common-tags'
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import { NextApiRequest, NextApiResponse } from 'next'
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import { z } from 'zod'
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import type { AiOptInLevel } from '@/hooks/misc/useOrgOptedIntoAi'
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import { getOrgAIDetails } from '@/lib/ai/ai-details'
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import { getModel } from '@/lib/ai/model'
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import { DEFAULT_COMPLETION_MODEL } from '@/lib/ai/model.utils'
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import { RLS_PROMPT } from '@/lib/ai/prompts'
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import { getTools } from '@/lib/ai/tools'
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import apiWrapper from '@/lib/api/apiWrapper'
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const policySchema = z.object({
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sql: z.string().describe('The generated Postgres CREATE POLICY statement.'),
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name: z.string().describe('The name of the policy.'),
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command: z
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.enum(['SELECT', 'INSERT', 'UPDATE', 'DELETE', 'ALL'])
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.describe('The SQL command this policy applies to.'),
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definition: z
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.string()
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.optional()
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.describe('The USING clause expression (for SELECT, UPDATE, DELETE).'),
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check: z.string().optional().describe('The WITH CHECK clause expression (for INSERT, UPDATE).'),
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action: z
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.enum(['PERMISSIVE', 'RESTRICTIVE'])
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.default('PERMISSIVE')
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.describe('Whether the policy is PERMISSIVE or RESTRICTIVE.'),
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roles: z.array(z.string()).default(['public']).describe('The roles this policy applies to.'),
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})
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const requestBodySchema = z.object({
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tableName: z.string().min(1),
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schema: z.string().default('public'),
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columns: z.array(z.string()).optional(),
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projectRef: z.string().min(1),
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connectionString: z.string().min(1),
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orgSlug: z.string().optional(),
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message: z.string().optional(),
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})
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async function handler(req: NextApiRequest, res: NextApiResponse) {
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const { method } = req
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switch (method) {
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case 'POST':
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return handlePost(req, res)
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default:
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res.setHeader('Allow', ['POST'])
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res.status(405).json({ data: null, error: { message: `Method ${method} Not Allowed` } })
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}
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}
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export async function handlePost(req: NextApiRequest, res: NextApiResponse) {
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const authorization = req.headers.authorization
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const accessToken = authorization?.replace('Bearer ', '')
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if (IS_PLATFORM && !accessToken) {
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return res.status(401).json({ error: 'Authorization token is required' })
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}
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const body = typeof req.body === 'string' ? JSON.parse(req.body) : req.body
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const { data, error: parseError } = requestBodySchema.safeParse(body)
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if (parseError) {
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return res.status(400).json({ error: 'Invalid request body', issues: parseError.issues })
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}
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const { tableName, schema, columns = [], projectRef, connectionString, orgSlug, message } = data
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let aiOptInLevel: AiOptInLevel = 'disabled'
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if (!IS_PLATFORM) {
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aiOptInLevel = 'schema'
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}
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if (IS_PLATFORM && orgSlug && authorization) {
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try {
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const { aiOptInLevel: orgAIOptInLevel } = await getOrgAIDetails({
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orgSlug,
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authorization,
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})
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aiOptInLevel = orgAIOptInLevel
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} catch (error) {
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return res.status(400).json({
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error: 'There was an error fetching your organization details',
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})
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}
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}
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try {
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const { modelParams, error: modelError } = await getModel({
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provider: 'openai',
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modelEntry: DEFAULT_COMPLETION_MODEL,
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})
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if (modelError) {
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return res.status(500).json({ error: modelError.message })
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}
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// Closes the remote MCP connection opened in getTools when generation is done,
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// if anything below throws, or if the client disconnects mid-generation so the
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// connection isn't held until generateText resolves on its own (mirrors the
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// request-scoped cleanup in generate-v4.ts).
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const toolsAbortController = new AbortController()
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req.on('close', () => toolsAbortController.abort())
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req.on('aborted', () => toolsAbortController.abort())
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// Fires when the response finishes or the connection drops.
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res.on('close', () => toolsAbortController.abort())
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try {
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const tools = await getTools({
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projectRef,
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connectionString,
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authorization,
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aiOptInLevel,
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accessToken,
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signal: toolsAbortController.signal,
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})
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const { experimental_output } = await generateText({
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...modelParams,
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stopWhen: stepCountIs(5),
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prompt: source`
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You are a Postgres RLS (Row Level Security) expert.
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Determine the most appropriate policies for the "${schema}"."${tableName}" table within a Supabase project.
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${columns.length > 0 ? `Table columns: ${columns.join(', ')}` : 'No column metadata provided.'}
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${message ? `User request: ${message}` : ''}
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RLS Guide: ${RLS_PROMPT}
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Requirements:
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- Use the available planning and schema tools (like "list_policies" or "list_tables") to inspect the "${schema}" schema and existing policies before generating new ones.
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- Ensure policies strictly adhere to the existing schema
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- Return a curated list of recommended CREATE POLICY statements as JSON.
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- Each policy must include: name, sql, command (SELECT/INSERT/UPDATE/DELETE/ALL), action (PERMISSIVE/RESTRICTIVE), roles (array of role names).
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- Include "definition" (USING clause expression without the USING keyword) for SELECT, UPDATE, DELETE policies.
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- Include "check" (WITH CHECK clause expression without the WITH CHECK keywords) for INSERT, UPDATE policies.
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- Avoid duplicating existing policies and reference the public schema and typical Supabase best practices when deciding the coverage.
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- Prefer PERMISSIVE policies unless a RESTRICTIVE policy is explicitly required
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`,
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tools,
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experimental_output: Output.object({
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schema: z.object({
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policies: z.array(policySchema),
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}),
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}),
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})
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// Add table and schema to each policy from the request
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const policies = (experimental_output?.policies ?? []).map((policy) => ({
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...policy,
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table: tableName,
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schema,
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}))
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return res.json(policies)
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} finally {
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toolsAbortController.abort()
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}
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} catch (error) {
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if (error instanceof Error) {
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console.error(`AI policy generation failed: ${error.message}`)
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return res.status(500).json({
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error: 'Failed to generate policy. Please try again.',
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})
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}
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return res.status(500).json({
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error: 'An unknown error occurred.',
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})
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}
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}
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const wrapper = (req: NextApiRequest, res: NextApiResponse) =>
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apiWrapper(req, res, handler, { withAuth: true })
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export default wrapper
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