"Information about Supabase cursor functionality" matching MCP servers:

MCP server that lets AI coding agents (Claude Code, Cursor, Cline) audit Supabase projects for security misconfigurations AND apply the fixes — without leaving the agent. Tools: audit_project, list_findings, preview_fix (BEGIN/ROLLBACK safety), apply_fix (with confirmation), apply_all_fixes (transactional bulk). Closes the audit-fix loop entirely in the agent — other Supabase scanners only report.

A local policy wrapper for Supabase MCP that secures access tokens and enforces strict execution models, including project allowlists and write-access restrictions. It provides a safety layer to prevent AI agents from accidentally executing migrations or writing SQL against production environments.

Enables AI agents to safely interact with Supabase through read-only and gated-write tools, with bounded queries, allowlists, and explicit project targeting.

A proof-of-concept attack that exploits Model Context Protocol (MCP) tool registration to achieve persistent agent poisoning in AI assistants like Cursor, embedding malicious instructions that persist across chat contexts without requiring tool execution.

Experimental read-only MCP for Supabase application data: memory_search, memory_get and memory_list_recent under user-bound PostgreSQL RLS. Setup and demo: https://github.com/jryski/Supabase_user_MCP/blob/main/docs/GETTING_STARTED.md . Public preview is POSIX-only and synthetic-only; native Windows, hosted OAuth, one-click installation and writes are not available.

Exposes your application's resources and tools as an MCP server using Supabase Auth, Postgres, and Row Level Security, allowing authorized users to connect via compatible MCP clients.

Enables MCP clients to safely inspect and query an explicitly allowlisted subset of a Postgres database through four read-only tools: a readiness check, table listing, column description, and typed row selection with filters, ordering, and paging. It runs over stdio for local clients or Streamable HTTP for separately managed ones, with bound parameters, bounded reads, and read-only transactions.

Enables safe, read-only SQL exploration and debugging on Supabase Edge Functions, respecting user JWTs. It inspects schemas, explains query plans, proposes RLS policies, and runs guarded queries without destructive operations.

Provides access to Shodan API functionality, enabling AI assistants to query information about internet-connected devices for cybersecurity research and threat intelligence.

Enables AI agents to conduct authorized penetration tests by providing scope-enforced access to Metasploit Framework's RPC, with tools for reconnaissance, exploitation, session management, and post-exploitation.

Provides Trivy security scanning capabilities through a standardized interface, allowing users to scan projects for vulnerabilities and automatically fix them by updating dependencies.

Enables agents to perform independent security review of AI-built apps by watching a GitHub repository and querying what the last reading found.

Enables AI agents to run read-only AWS security audits and receive normalized, severity-ranked findings about account posture, such as stale access keys, missing MFA, public buckets, open security groups, and CloudTrail coverage.

A robust Model Control Protocol server that enables AI agents to access real-time cyber threat intelligence and detailed information about vulnerabilities, threat actors, malware, and other cyber-security entities.

A read-only MCP server for the Qualys PCI Merchant API that lets LLM assistants answer questions about PCI compliance posture, such as which hosts are failing PCI or listing high findings.

Security MCP server with 300+ rules for AI-generated code. Scans Next.js, Supabase, Clerk, Stripe, Prisma, Hono, GraphQL and 20+ modules. Zero config, runs locally.

A Model Context Protocol (MCP) server for Socket integration, allowing AI assistants to efficiently check dependency vulnerability scores and security information.

Audits PostgreSQL/Supabase schemas for security issues like missing RLS, permissive policies, and sensitive data exposure during AI conversations.

Exposes Microsoft 365 privacy/compliance audit checks as MCP tools, enabling natural language queries about tenant configuration, orphaned documents, Conditional Access policies, DLP policies, and Copilot usage.

Provides real-time security risk assessment for AI coding prompts, analyzing potential dangers, blast radius, and complexity before code execution in Cursor.