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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 11 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Generates standardized tool schemas from PayPal API operations and registers them with 7+ AI frameworks (OpenAI, LangChain, Anthropic, Bedrock, Vercel AI SDK, CrewAI) through framework-specific adapters. Uses a hub-and-spoke architecture where a shared core PayPal operation layer delegates to framework-specific modules that translate PayPal tools into each framework's native function-calling format (OpenAI's tool_choice, LangChain's BaseTool, Anthropic's tool_use_block_delta, etc.), enabling single-codebase deployment across heterogeneous AI stacks.
Unique: Implements a symmetric dual-language (TypeScript/Python) hub-and-spoke architecture with 7+ framework adapters that all delegate to shared core PayPal API logic, eliminating code duplication while maintaining framework-native semantics. Each framework module (ai-sdk, mcp, langchain, openai, bedrock, crewai) provides thin translation layers rather than reimplementing PayPal operations.
vs alternatives: Provides unified PayPal integration across more frameworks (7+) than point solutions like OpenAI's official integrations, with true code parity between TypeScript and Python rather than separate implementations.
Exposes PayPal operations as an MCP server that implements the Model Context Protocol specification, allowing any MCP-compatible client (Claude, custom agents, IDE extensions) to discover and invoke PayPal tools via standardized JSON-RPC 2.0 messaging. The MCP server wraps the shared PayPal core layer and translates tool invocations into PayPal REST API calls, handling authentication, error serialization, and response formatting according to MCP resource/tool semantics.
Unique: Implements MCP server as a first-class integration pattern (not an afterthought) with dedicated @paypal/agent-toolkit/mcp export, enabling protocol-standardized access to 31 PayPal operations. Reuses shared core PayPal logic via the same hub-and-spoke pattern as framework adapters, ensuring consistency between MCP and direct library usage.
vs alternatives: Provides standardized MCP access to PayPal APIs before most payment providers, enabling future-proof integration with any MCP-compatible AI client rather than being locked into specific frameworks.
Implements consistent error handling and response parsing in the shared core layer that translates PayPal REST API responses (including error codes, validation failures, rate limiting) into framework-agnostic error objects. Each framework adapter wraps core errors in framework-specific exception types (OpenAI's APIError, LangChain's ToolException, etc.) while preserving PayPal error details. Supports automatic retry logic for transient failures (rate limits, timeouts) and provides detailed error context for debugging.
Unique: Implements error handling in the shared core layer and translates to framework-specific exceptions in adapters, ensuring consistent error semantics across all 7+ frameworks. Distinguishes transient errors (rate limits, timeouts) from permanent failures (invalid credentials, invalid operations).
vs alternatives: Provides unified error handling across frameworks, whereas point solutions require developers to implement error handling separately for each framework integration.
Provides 7 distinct invoice operations (create, send, update, cancel, search, get details, record payment) that map to PayPal's Invoice REST API endpoints. Each operation is implemented as a typed function in the shared core layer that handles request validation, API authentication, and response parsing. Supports invoice templates, payment tracking, and status transitions (draft, sent, paid, cancelled) with full parameter mapping to PayPal's invoice schema.
Unique: Implements invoice operations as typed, validated functions in the shared core layer with consistent error handling and response parsing across all 7 invoice operations. Supports both direct library calls and framework-agnostic invocation through any of the 7+ framework adapters.
vs alternatives: Provides unified invoice automation across TypeScript and Python with identical APIs, whereas most payment SDKs require separate implementations or lack invoice-specific operations entirely.
Implements 5 order and payment operations (create order, capture payment, authorize payment, refund, get order details) that handle the full payment lifecycle through PayPal's Orders API. Each operation validates input parameters, routes requests to the appropriate PayPal endpoint, and parses responses into typed objects. Supports payment intent selection (CAPTURE vs AUTHORIZE), payer information, and transaction status tracking with error handling for declined payments and authorization failures.
Unique: Implements order operations with explicit AUTHORIZE vs CAPTURE routing, allowing agents to make payment intent decisions dynamically. Shared core layer handles all validation and API communication, enabling consistent behavior across framework adapters.
vs alternatives: Provides both authorization and capture operations in a single toolkit, whereas many payment SDKs bundle them or require separate API calls, making it easier for agents to implement fraud-checking workflows.
Provides 8 subscription operations and 3 catalog operations for managing recurring billing and product definitions. Subscription operations include create plan, create subscription, update subscription, cancel subscription, suspend subscription, reactivate subscription, and get subscription details. Catalog operations handle product creation, updates, and retrieval. All operations validate parameters against PayPal's subscription schema (billing cycles, pricing tiers, trial periods) and handle subscription state transitions (APPROVAL_PENDING, ACTIVE, SUSPENDED, CANCELLED).
Unique: Implements subscription operations with explicit state machine handling (APPROVAL_PENDING → ACTIVE → SUSPENDED/CANCELLED) and supports multi-tier pricing within single subscription plans. Catalog operations are integrated into the same toolkit rather than as separate dependencies.
vs alternatives: Provides unified subscription and product management in one toolkit, whereas most payment SDKs separate billing and catalog concerns, requiring developers to coordinate between multiple APIs.
Implements 3 dispute operations (get dispute details, update dispute status, provide evidence) that handle PayPal's dispute resolution workflow. Operations support dispute status tracking (OPEN, UNDER_REVIEW, RESOLVED, ESCALATED), evidence submission with file attachments, and status transitions. The shared core layer validates evidence types (PROOF_OF_DELIVERY, INVOICE, REFUND_CONFIRMATION, etc.) and handles multipart form data for file uploads to PayPal's Disputes API.
Unique: Implements dispute operations with explicit evidence type validation and multipart form data handling for file uploads, enabling agents to submit evidence without manual file management. Integrated into the same toolkit as payment operations for unified dispute-to-payment workflows.
vs alternatives: Provides programmatic dispute evidence submission, whereas most payment SDKs only expose read-only dispute status, requiring manual evidence uploads through PayPal's dashboard.
Provides 3 shipment operations (add tracking information, update shipment status, get shipment details) that integrate with PayPal's Tracking API for order fulfillment. Operations support carrier selection (USPS, UPS, FedEx, DHL, etc.), tracking number submission, and status transitions (SHIPPED, IN_TRANSIT, DELIVERED, RETURNED). The shared core layer validates carrier codes and tracking formats, enabling agents to automatically update customer shipment status after payment capture.
Unique: Implements shipment operations with carrier code validation and status machine handling, enabling agents to automatically update PayPal with fulfillment status without manual carrier integration. Integrated into the same toolkit as order operations for end-to-end fulfillment workflows.
vs alternatives: Provides programmatic shipment tracking updates to PayPal, whereas most payment SDKs lack fulfillment integration, requiring separate logistics API calls and manual PayPal updates.
+3 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 PayPal at 26/100.
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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