| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 12 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Intercepts tool calls from MCP clients before execution, applies configurable security policies (allowlists, denylists, parameter validation rules), and either permits or blocks execution based on policy evaluation. Implements a proxy pattern that sits between the MCP client and server, inspecting the tool name, parameters, and context to enforce organizational security boundaries without modifying the underlying MCP protocol.
Unique: Implements MCP-native tool-call interception at the protocol level rather than wrapping individual tool implementations, allowing centralized policy enforcement across heterogeneous MCP servers without modifying server code
vs alternatives: Provides MCP-specific security enforcement that works across any MCP server without code changes, whereas generic API gateways require per-endpoint configuration and lack MCP protocol semantics
Routes tool calls flagged by policy rules to a human reviewer queue, pausing execution until explicit approval or rejection is provided. Implements a callback-based workflow where blocked or high-risk calls are held in a state machine, allowing async human review via API or UI integration, then resuming or aborting the original MCP request based on the decision.
Unique: Integrates human approval as a first-class workflow primitive in the MCP proxy layer, allowing approval gates to be defined declaratively in policy without custom application code
vs alternatives: Provides MCP-native approval workflows that pause execution at the protocol level, whereas custom approval systems typically require wrapping individual tool implementations or building separate orchestration layers
Validates MCP tool call requests and responses against schema definitions, ensuring type correctness and structural integrity. Implements schema-based validation where tool definitions include parameter schemas and response schemas, and the proxy validates incoming requests and outgoing responses against these schemas. Supports JSON Schema or similar schema formats and provides detailed validation error messages.
Unique: Provides MCP-level schema validation that works across all tools without requiring per-tool implementation, enabling centralized type safety enforcement
vs alternatives: Validates schemas at the protocol level before tool execution, whereas per-tool validation requires implementing validation in each tool and may miss edge cases
Routes tool calls to appropriate MCP servers based on tool availability, load, or custom routing rules, implementing a load balancing strategy that distributes calls across multiple server instances. Supports round-robin, least-connections, and custom routing algorithms. Maintains health checks on server instances and automatically removes unhealthy servers from the routing pool.
Unique: Provides MCP-level load balancing that works across heterogeneous tool servers without requiring per-tool routing logic, enabling transparent scaling and failover
vs alternatives: Routes at the MCP protocol level before tool execution, whereas generic load balancers (nginx, HAProxy) lack MCP semantics and cannot make tool-aware routing decisions
Logs all tool call attempts, policy evaluations, approval decisions, and execution results to a structured audit trail with timestamps, actor information, and decision rationale. Implements a logging pipeline that captures both successful and blocked calls, enabling forensic analysis, compliance reporting, and security investigations. Logs are structured (JSON) for easy querying and integration with SIEM systems.
Unique: Provides MCP-level audit logging that captures the full lifecycle of tool calls (request, policy evaluation, approval, execution, result) in a single structured log, enabling end-to-end traceability without instrumenting individual tools
vs alternatives: Captures MCP protocol-level events that generic API logging cannot see, providing visibility into policy decisions and approval workflows that are invisible to downstream tool implementations
Allows security policies to be defined declaratively (likely JSON or YAML) with support for composing multiple rules (allowlists, denylists, parameter constraints, rate limits) into a cohesive policy. Policies are evaluated against tool call metadata at runtime, supporting logical operators (AND, OR) and context-aware conditions (e.g., 'allow only if user role is admin'). Policies are loaded at proxy startup and can be versioned for audit purposes.
Unique: Provides a declarative policy language tailored to MCP tool calls, allowing non-developers to define security rules without understanding the underlying proxy architecture
vs alternatives: Offers MCP-specific policy syntax that understands tool call semantics (tool name, parameters, context), whereas generic API gateway policies require manual mapping of tool calls to API endpoints
Evaluates tool call requests in the context of the requesting agent or user identity, applying identity-based access control rules. Extracts identity information from MCP request metadata (e.g., client ID, user ID, role) and uses it to make allow/block decisions, enabling fine-grained access control where different agents have different tool permissions. Supports role-based access control (RBAC) and attribute-based access control (ABAC) patterns.
Unique: Integrates identity-based access control directly into the MCP proxy, allowing identity to be a first-class dimension of tool call filtering without requiring custom authorization logic in each tool
vs alternatives: Provides MCP-native identity-based filtering that works across heterogeneous tools, whereas per-tool authorization requires implementing access control in each tool implementation
Validates and optionally sanitizes parameters in tool calls before execution, enforcing constraints like type checking, value ranges, string length limits, and regex patterns. Implements a schema-based validation approach where tool parameters are validated against a schema definition, rejecting calls with invalid parameters and optionally logging violations. Supports both strict validation (reject invalid calls) and lenient modes (log and allow).
Unique: Provides schema-based parameter validation at the MCP proxy layer, catching invalid parameters before they reach tool implementations and enabling centralized validation logic
vs alternatives: Validates parameters at the protocol level before tool execution, whereas per-tool validation requires implementing validation in each tool and may miss edge cases
+4 more capabilities
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 @getcordon/core at 25/100.
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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
+1 more capabilities