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| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 8 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Intercepts all Model Context Protocol tool invocations at the gateway layer before execution, applying configurable governance policies to approve, deny, or modify tool calls based on security rules and compliance requirements. Uses a proxy architecture that sits between LLM agents (CrewAI, LangChain) and MCP servers, inspecting call signatures and payloads against policy definitions without requiring changes to upstream agent code.
Unique: Implements MCP-specific governance as a transparent proxy layer with non-repudiation guarantees via ED25519 signatures, rather than relying on agent-level access control or LLM prompt-based restrictions. Integrates with ABS Core NRaaS to cryptographically bind tool call decisions to identifiable actors.
vs alternatives: Unlike prompt-based tool restrictions (easily bypassed) or agent-level ACLs (require code changes), this gateway approach provides cryptographically-auditable governance that applies uniformly across all agents and cannot be circumvented by prompt injection.
Cryptographically signs all tool call governance decisions (approval, denial, modification) using ED25519 digital signatures, creating an immutable audit trail that proves who authorized or rejected each tool invocation and when. Each decision is bound to an actor identity and cannot be forged or altered retroactively, satisfying compliance requirements for accountability in regulated environments.
Unique: Implements Non-Repudiation as a Service (NRaaS) specifically for MCP tool governance, using ED25519 signatures to bind decisions to actor identities with cryptographic certainty. This is distinct from generic audit logging because signatures are mathematically unforgeable and can be verified by external parties.
vs alternatives: Standard audit logs can be tampered with or deleted; ED25519 signatures create cryptographic proof that a decision was made by a specific actor at a specific time, satisfying compliance requirements that generic logging cannot meet.
Evaluates incoming MCP tool calls against a configurable policy engine that can allow, block, or transform tool invocations based on rules matching tool name, arguments, caller identity, resource usage, or other contextual signals. Policies are evaluated before tool execution, enabling fine-grained control over what agents can do without requiring changes to agent code or LLM prompts.
Unique: Provides MCP-specific policy evaluation at the gateway layer, allowing rules to match on MCP-specific metadata (tool name, schema, arguments) rather than generic HTTP/API patterns. Integrates with ABS Core for policy storage and evaluation, enabling centralized governance across multiple agents.
vs alternatives: Unlike agent-level tool restrictions (which require code changes) or LLM prompt-based controls (which are easily bypassed), gateway-level policy enforcement applies uniformly and cannot be circumvented by prompt injection or agent code modification.
Manages tool access permissions across multiple AI agents based on actor identity, role, or team membership, ensuring that different agents or users can only invoke tools they are authorized to use. Uses identity context from the MCP request to evaluate role-based access control (RBAC) policies, enabling fine-grained delegation of tool access without modifying individual agent configurations.
Unique: Implements role-based access control at the MCP gateway layer, allowing fine-grained tool access decisions based on actor identity without requiring changes to individual agent code. Integrates with ABS Core identity management to support centralized role definitions across multiple agents and teams.
vs alternatives: Unlike agent-level tool restrictions (which require per-agent configuration) or LLM-based access control (which is not cryptographically enforceable), gateway-level RBAC provides centralized, auditable, and tamper-proof tool access control.
Records comprehensive audit logs of all tool call governance decisions, including tool name, arguments, actor identity, decision (allow/deny/modify), timestamp, and ED25519 signature proving the decision was made by an authorized entity. Logs are structured for compliance reporting and can be exported for external audit or forensic analysis.
Unique: Combines comprehensive audit logging with ED25519 cryptographic signatures, creating tamper-proof records of tool call governance decisions that satisfy compliance requirements. Each log entry is cryptographically bound to the decision maker and timestamp, making it impossible to forge or alter logs retroactively.
vs alternatives: Standard audit logs can be tampered with or deleted; cryptographically-signed audit logs provide mathematical proof that a record was created by an authorized entity at a specific time, satisfying compliance requirements that generic logging cannot meet.
Acts as a transparent proxy between LLM agents and MCP servers, intercepting all MCP protocol messages (JSON-RPC format), applying governance policies, and forwarding approved calls to the actual MCP server endpoints. Handles request/response transformation, error handling, and timeout management without requiring agents to be aware of the proxy layer.
Unique: Implements MCP-specific proxying that understands the MCP protocol (JSON-RPC, tool schemas, context protocol) rather than generic HTTP proxying, enabling governance decisions based on MCP-specific metadata like tool name, schema, and arguments.
vs alternatives: Unlike generic HTTP proxies (which cannot understand MCP semantics) or agent-level tool wrappers (which require code changes), MCP gateway proxying provides transparent governance that works with any MCP-compatible agent without modification.
Provides native integration points with CrewAI and LangChain agent frameworks, allowing these frameworks to route tool calls through the MCP gateway for governance without requiring custom code. Handles framework-specific tool registration, context passing, and response handling to ensure seamless integration with existing agent code.
Unique: Provides native integration with CrewAI and LangChain rather than requiring agents to manually route calls through the gateway, enabling governance to be added with minimal code changes. Handles framework-specific tool registration and context passing transparently.
vs alternatives: Unlike generic MCP client libraries (which require agents to manually route calls), framework-specific integration allows governance to be added as a transparent layer that works with existing agent code.
Generates compliance reports and audit evidence demonstrating that AI tool usage meets regulatory requirements (NIST, HIPAA, SOX, GDPR, etc.) by providing cryptographically-signed records of tool call governance decisions, actor accountability, and policy enforcement. Reports can be exported for external audit or regulatory review.
Unique: Combines cryptographically-signed audit logs with compliance reporting to provide auditors with mathematical proof that AI tool usage meets regulatory requirements. Uses ED25519 signatures to create tamper-proof evidence of governance and accountability.
vs alternatives: Unlike generic audit logs (which can be tampered with) or self-attestations (which lack proof), cryptographically-signed compliance reports provide mathematical evidence that governance controls are in place and functioning correctly.
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 @oconnector/mcp-gateway at 28/100.
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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
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