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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes Adfin's payment processing, invoicing, and accounting APIs through the Model Context Protocol (MCP) server interface, enabling LLM agents and AI tools to read/write payment data via standardized tool-calling conventions. Implements MCP resource handlers that map Adfin REST endpoints to callable tools with schema-based argument validation, allowing Claude and other MCP-compatible clients to query payment status, retrieve invoices, and trigger accounting reconciliations without direct API knowledge.
Unique: Bridges Adfin's payment/invoicing/accounting APIs into the MCP ecosystem, enabling LLM agents to access financial data through standardized tool-calling rather than custom integrations. Uses MCP's resource and tool handler patterns to abstract Adfin's REST API surface into agent-friendly callable functions with schema validation.
vs alternatives: Provides native MCP integration for Adfin (vs. building custom API wrappers), enabling seamless Claude integration without additional middleware or API gateway layers
Implements MCP tool handlers that query Adfin's payment endpoints to retrieve real-time payment status, transaction history, and payment method details. Translates MCP tool calls with filters (date range, payment ID, status) into Adfin REST API requests, parses JSON responses, and returns structured payment records to the LLM client for analysis or further action.
Unique: Exposes Adfin payment queries through MCP's tool-calling interface with schema-based filtering, allowing LLMs to construct complex payment queries (date ranges, status filters) without understanding Adfin's REST API structure.
vs alternatives: Simpler than building custom REST client wrappers — MCP handles serialization and error handling, and Claude can naturally express payment queries in plain language
Provides MCP tool handlers for creating, updating, and retrieving invoices through Adfin's invoicing API. Accepts structured invoice data (client name, line items, due date, tax settings) from the LLM client, validates against Adfin's schema, submits to Adfin's invoice creation endpoint, and returns the created invoice ID and PDF URL. Supports invoice retrieval by ID and bulk listing with filters.
Unique: Abstracts Adfin's invoice API into natural-language-friendly MCP tools, enabling LLMs to construct invoices by describing business logic (e.g., 'create invoice for 40 hours at $150/hr') rather than manually specifying line items.
vs alternatives: Faster than manual invoice creation in Adfin UI; integrates directly with LLM reasoning, allowing agents to calculate totals, apply discounts, and generate invoices in a single workflow
Implements MCP tool handlers that trigger Adfin's accounting reconciliation engine, which matches payments against invoices, detects discrepancies, and syncs transaction data with accounting systems (QuickBooks, Xero, etc.). Accepts reconciliation parameters (date range, account filter) and returns reconciliation status, matched/unmatched transactions, and any errors requiring manual review.
Unique: Exposes Adfin's reconciliation engine as an MCP tool, allowing LLM agents to trigger complex multi-step accounting workflows (match payments, detect discrepancies, sync to external systems) with a single natural-language request.
vs alternatives: Eliminates manual reconciliation steps by automating payment-to-invoice matching and accounting system sync; LLM agents can monitor reconciliation status and escalate issues without human intervention
Provides MCP tool handlers that manage multi-currency payments and tax calculations through Adfin's currency and tax APIs. Accepts payment/invoice requests with currency codes and tax jurisdictions, applies real-time exchange rates and tax rules (VAT, GST, sales tax), and returns tax-inclusive totals and currency conversions. Supports tax compliance reporting for multiple jurisdictions.
Unique: Integrates Adfin's tax and currency APIs into MCP tools, enabling LLMs to automatically apply correct tax rates and exchange rates based on jurisdiction and currency without manual lookup or calculation.
vs alternatives: Reduces tax compliance errors by automating jurisdiction-specific tax calculations; LLM agents can generate compliant invoices for international clients without accounting expertise
Exposes MCP tool handlers for managing payment methods (credit cards, bank accounts, digital wallets) and customer records in Adfin. Allows creation, update, and retrieval of customer profiles with payment method associations, tokenization of sensitive payment data, and validation of payment method eligibility. Integrates with Adfin's PCI compliance framework to ensure secure handling of payment credentials.
Unique: Abstracts Adfin's PCI-compliant payment method tokenization into MCP tools, allowing LLMs to manage customer payment methods without ever handling raw payment credentials. Uses token-based references instead of exposing sensitive data.
vs alternatives: Safer than custom payment method handling — Adfin's PCI compliance framework is built-in; LLM agents can manage payment methods without security risks or compliance violations
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 Adfin at 24/100.
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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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