| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 7 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Implements a stdio proxy that intercepts Model Context Protocol messages between client and server, allowing governance policies to be applied to tool calls before they reach the underlying MCP server. Uses a passthrough architecture that wraps stdin/stdout streams, parsing incoming JSON-RPC messages and applying rule-based filtering or modification before forwarding to the actual MCP server implementation.
Unique: Implements governance as a transparent stdio proxy layer that intercepts MCP protocol messages without requiring server-side modifications, using JSON-RPC message parsing to apply rule-based filtering at the protocol level before tool execution
vs alternatives: Lighter-weight than building governance into each MCP server implementation, and more flexible than client-side filtering since it operates at the protocol boundary with full visibility into tool calls
Validates incoming tool call requests against defined schemas before forwarding to the MCP server, checking parameter types, required fields, and constraint violations. Uses JSON Schema or similar validation patterns to ensure tool invocations conform to governance policies, rejecting non-compliant requests with structured error responses that maintain MCP protocol compatibility.
Unique: Operates at the MCP protocol boundary to validate tool parameters before execution, maintaining full protocol compatibility while enforcing schema constraints that would otherwise require server-side implementation
vs alternatives: Centralized validation at the proxy layer prevents invalid requests from reaching backend services, whereas server-side validation requires changes to each tool implementation
Enforces role-based access control (RBAC) on tool invocations by mapping client identities or contexts to allowed tool sets, blocking unauthorized tool calls before they reach the MCP server. Implements policy matching logic that evaluates tool names, user roles, or other context attributes against a governance ruleset, returning permission-denied responses for unauthorized access attempts.
Unique: Implements RBAC at the MCP proxy layer, allowing centralized tool access policies without modifying individual tool implementations or requiring client-side enforcement
vs alternatives: More maintainable than distributing access control logic across multiple MCP servers, and more reliable than client-side enforcement since policies are enforced at the protocol boundary
Applies rate limiting and quota policies to tool invocations, tracking usage per user, tool, or time window and rejecting requests that exceed defined limits. Uses in-memory counters or sliding window algorithms to enforce quotas, returning rate-limit error responses that maintain MCP protocol compatibility while preventing resource exhaustion or abuse.
Unique: Enforces rate limiting at the MCP protocol boundary using in-memory counters, providing immediate feedback without requiring backend service changes or external dependencies for single-instance deployments
vs alternatives: Simpler to deploy than distributed rate limiting systems, but requires external state coordination for multi-instance setups; more responsive than backend-side rate limiting due to proxy-level enforcement
Captures detailed audit logs of all tool invocations passing through the proxy, recording request parameters, execution results, governance decisions, and timestamps. Emits structured log events that can be forwarded to external logging systems, providing visibility into tool usage patterns, policy violations, and execution outcomes for compliance and debugging purposes.
Unique: Provides transparent audit logging at the MCP protocol boundary, capturing all tool invocations and governance decisions without requiring instrumentation of individual tools or server code
vs alternatives: More comprehensive than application-level logging since it captures all tool calls at the protocol level; easier to implement than distributed tracing across multiple services
Transforms or enriches MCP protocol messages as they pass through the proxy, adding metadata, modifying parameters, or injecting context information. Implements message interception hooks that allow policies to rewrite tool call requests (e.g., adding user context to parameters) or responses (e.g., filtering sensitive fields) while maintaining protocol compatibility.
Unique: Intercepts MCP protocol messages at the proxy layer to apply transformations without modifying client or server code, enabling context injection and response filtering at the protocol boundary
vs alternatives: More flexible than client-side transformation since it operates on the actual protocol messages; more maintainable than server-side transformation since policies are centralized in the proxy
Provides a configuration interface for defining and managing governance policies (access control, rate limits, validation rules, audit settings) that are applied to tool calls. Supports loading policies from configuration files, environment variables, or programmatic APIs, allowing policies to be updated without modifying proxy code or restarting the process (where supported).
Unique: Centralizes governance policy definitions in a configuration layer, allowing policies to be managed separately from proxy code and supporting multiple configuration sources (files, environment, API)
vs alternatives: More maintainable than hardcoding policies in proxy logic; more flexible than server-side policy management since policies are applied uniformly across all tools
Executes SQL queries against Supabase PostgreSQL instances through the Model Context Protocol, translating natural language or structured query requests into parameterized SQL statements. Uses MCP's tool-calling interface to expose database operations as callable functions with schema validation, enabling LLM agents to perform CRUD operations, joins, and aggregations with automatic connection pooling and credential management through Supabase client SDK.
Unique: Exposes Supabase PostgreSQL as MCP tools with automatic credential injection from Supabase client SDK, eliminating manual connection string management and enabling seamless LLM-to-database queries within Claude or compatible agents
vs alternatives: Tighter integration than generic SQL MCP servers because it leverages Supabase's built-in authentication and connection pooling rather than requiring separate database credential configuration
Exposes Supabase Auth session state and user metadata through MCP tools, allowing agents to inspect current authentication context, retrieve user profiles, and trigger auth-related operations. Integrates with Supabase's JWT-based auth system to validate sessions and access user claims without re-authenticating, using the Supabase client's built-in session management.
Unique: Integrates Supabase's JWT-based auth system directly into MCP tool interface, allowing agents to inspect and act on auth state without managing separate credential stores or re-authentication flows
vs alternatives: More seamless than generic auth MCP servers because it leverages Supabase's built-in session management and avoids redundant credential passing between agent and auth system
Invokes Supabase Edge Functions (serverless TypeScript/JavaScript functions) through MCP tools, passing parameters and receiving results with optional streaming support. Uses Supabase's edge function HTTP API to trigger functions with automatic authentication headers and response parsing, enabling agents to execute custom business logic without embedding it in the agent itself.
Supabase scores higher at 42/100 vs vloex-mcp-proxy at 24/100. vloex-mcp-proxy leads on ecosystem, while Supabase is stronger on quality.
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Unique: Exposes Supabase Edge Functions as MCP tools with automatic authentication and response parsing, allowing agents to invoke custom serverless logic without managing HTTP clients or credential injection
vs alternatives: More integrated than generic HTTP MCP tools because it handles Supabase-specific authentication, error handling, and response formatting automatically
Subscribes to real-time changes on Supabase tables through MCP's event streaming interface, using Supabase's PostgreSQL LISTEN/NOTIFY mechanism to push INSERT, UPDATE, and DELETE events to agents. Maintains persistent WebSocket connections and filters events by table and row-level policies, enabling agents to react to database changes without polling.
Unique: Bridges Supabase's PostgreSQL LISTEN/NOTIFY real-time system with MCP's tool interface, enabling agents to subscribe to database changes without managing WebSocket connections or event serialization
vs alternatives: More efficient than polling-based approaches because it uses Supabase's native real-time infrastructure rather than repeated database queries
Manages files in Supabase Storage buckets through MCP tools, supporting upload, download, list, and delete operations with automatic authentication and path-based access control. Uses Supabase's S3-compatible storage API with built-in support for public/private buckets and signed URLs for temporary access, enabling agents to handle file I/O without managing cloud storage credentials.
Unique: Exposes Supabase Storage's S3-compatible API as MCP tools with automatic authentication and signed URL generation, eliminating the need for agents to manage cloud storage credentials or generate temporary access tokens
vs alternatives: More integrated than generic S3 MCP tools because it leverages Supabase's built-in bucket policies and authentication rather than requiring separate AWS credentials
Performs semantic similarity searches on vector embeddings stored in Supabase PostgreSQL using pgvector extension, translating natural language queries into embedding vectors and executing cosine/L2 distance searches. Integrates with embedding providers (OpenAI, Cohere) or uses pre-computed embeddings, enabling agents to retrieve semantically similar documents or records without full-text search limitations.
Unique: Integrates pgvector directly into MCP tools with automatic embedding generation and distance calculation, enabling agents to perform semantic search without managing separate vector database infrastructure
vs alternatives: More efficient than external vector databases (Pinecone, Weaviate) for Supabase users because it colocates embeddings with relational data, reducing network latency and simplifying data synchronization
Exposes Supabase database schema information through MCP tools, allowing agents to discover table structures, column types, constraints, and relationships without manual schema documentation. Queries PostgreSQL information_schema and Supabase metadata tables to dynamically generate schema descriptions, enabling agents to construct valid queries and understand data relationships.
Unique: Queries Supabase's PostgreSQL information_schema directly through MCP tools, enabling agents to dynamically discover and adapt to database schemas without pre-configured schema definitions
vs alternatives: More flexible than static schema definitions because it reflects live database state, including recent migrations or schema changes
Enforces Supabase Row-Level Security policies within agent queries, ensuring that agents can only access rows permitted by RLS rules defined in the database. Evaluates policies based on authenticated user context (JWT claims, user ID) and applies WHERE clause filters automatically, preventing unauthorized data access at the database layer rather than application layer.
Unique: Delegates authorization enforcement to PostgreSQL RLS policies rather than implementing authorization in agent code, ensuring that data access rules are centralized and cannot be bypassed by agent logic
vs alternatives: More secure than application-level authorization because RLS is enforced at the database layer, preventing accidental data leaks even if agent code has bugs
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