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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>
80 lines
2.3 KiB
TypeScript
80 lines
2.3 KiB
TypeScript
import { ToolSet } from 'ai'
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import { IS_PLATFORM } from 'common'
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import { filterToolsByOptInLevel } from '../tool-filter'
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import { getFallbackTools } from './fallback-tools'
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import { getIncidentTools } from './incident-tools'
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import { getMcpTools } from './mcp-tools'
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import { getSchemaTools } from './schema-tools'
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import { getStudioTools } from './studio-tools'
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import { AiOptInLevel } from '@/hooks/misc/useOrgOptedIntoAi'
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export const getTools = async ({
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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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baseUrl,
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signal,
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}: {
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projectRef: string
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connectionString: string
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authorization?: string
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aiOptInLevel: AiOptInLevel
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accessToken?: string
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baseUrl?: string
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// Required: tools fetched from the remote MCP server hold an HTTP connection
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// that is closed when this signal aborts (i.e. when the request ends).
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signal: AbortSignal
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}) => {
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// Always include studio tools
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let tools: ToolSet = getStudioTools({ projectRef, connectionString, authorization, aiOptInLevel })
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// If self-hosted, only add fallback tools
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if (!IS_PLATFORM) {
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tools = {
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...tools,
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...getFallbackTools({
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projectRef,
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connectionString,
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authorization,
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includeSchemaMetadata: aiOptInLevel !== 'disabled',
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}),
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}
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} else if (accessToken) {
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// If platform, fetch MCP and other platform specific tools. The MCP tools
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// may be fetched from the remote MCP server over the network (see
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// `USE_REMOTE_MCP`), so a failure there (outage, timeout, auth) should
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// degrade gracefully to the remaining tools rather than break the entire
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// assistant.
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let mcpTools: ToolSet = {}
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try {
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mcpTools = await getMcpTools({
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accessToken,
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projectRef,
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aiOptInLevel,
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signal,
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})
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} catch (error) {
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console.error('Failed to fetch MCP tools:', error)
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}
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tools = {
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...tools,
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...mcpTools,
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...getSchemaTools({
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projectRef,
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connectionString,
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authorization,
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}),
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...(baseUrl ? getIncidentTools({ baseUrl }) : {}),
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}
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}
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// Filter all tools based on the (potentially modified) AI opt-in level
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const filteredTools: ToolSet = filterToolsByOptInLevel(tools, aiOptInLevel)
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return filteredTools
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}
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