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| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 7 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Registers Xero API endpoints as callable tools in MCP-compatible clients by exposing a schema-driven tool registry that maps Xero REST API operations to standardized MCP tool definitions. The server introspects Xero's API specification and generates tool schemas with parameter validation, enabling LLM agents to discover and invoke Xero operations (create invoice, fetch contacts, update accounts) without hardcoded integrations. Uses MCP's tool_call protocol to mediate between client requests and Xero API execution.
Unique: Implements MCP as a first-class integration layer for Xero, allowing LLM agents to treat Xero operations as native tools rather than requiring custom API wrappers. Uses MCP's standardized tool schema format to expose Xero's full REST API surface dynamically.
vs alternatives: Provides tighter LLM-to-Xero integration than generic REST API clients because MCP's tool protocol is optimized for agent reasoning and function calling, vs. requiring agents to construct raw HTTP requests.
Manages Xero OAuth2 authentication lifecycle including initial authorization flow, access token storage, and automatic token refresh before expiration. The server implements the OAuth2 authorization code flow, stores refresh tokens securely (or via configurable persistence), and transparently refreshes expired tokens before API calls fail. Handles Xero's token expiration (typically 30 minutes) and refresh token rotation to maintain uninterrupted API access for long-running agent sessions.
Unique: Integrates OAuth2 token lifecycle management directly into the MCP server, eliminating the need for agents or clients to handle credential refresh logic. Transparently manages Xero's 30-minute token expiration within the server's request pipeline.
vs alternatives: Simpler than requiring agents to implement OAuth2 refresh logic themselves, and more secure than storing long-lived API keys because OAuth2 tokens are short-lived and can be revoked.
Maps Xero REST API endpoints to callable tool operations with automatic parameter validation and type coercion. The server defines schemas for each Xero operation (e.g., CreateInvoice, GetContact, UpdateAccount) specifying required/optional parameters, data types, and constraints. Validates incoming tool_call requests against these schemas before forwarding to Xero, catching malformed requests early and providing clear error messages. Handles Xero-specific quirks like date formatting (YYYY-MM-DD), enum constraints (invoice status), and nested object structures.
Unique: Implements Xero-specific validation rules (date formats, enum constraints, nested object structures) within the MCP server, preventing invalid requests from reaching Xero's API and providing agents with actionable validation errors.
vs alternatives: More robust than agents directly calling Xero's REST API because validation happens server-side before transmission, reducing failed requests and improving agent reliability.
Transforms Xero API responses into MCP-compatible tool_result format and handles Xero-specific error conditions. The server normalizes Xero's response structure (often nested with metadata), extracts relevant data fields, and formats results as JSON for the MCP client. Implements error handling for common Xero failures (401 Unauthorized, 429 Rate Limited, 400 Bad Request) with retry logic for transient errors and clear error messages for permanent failures. Maps Xero HTTP status codes to MCP error semantics.
Unique: Implements Xero-aware error handling and response normalization within the MCP server, abstracting Xero's API quirks from agents and providing consistent, MCP-compatible responses regardless of underlying Xero behavior.
vs alternatives: Reduces agent complexity by centralizing error handling and retry logic in the server, vs. requiring agents to implement Xero-specific error recovery.
Enables agents to execute multiple Xero API operations in sequence with optional transaction semantics (all-or-nothing execution). The server queues multiple tool_call requests, executes them in order, and can optionally rollback all operations if any step fails. Implements idempotency tracking to prevent duplicate operations if requests are retried. Useful for workflows like 'create invoice, add line items, mark as sent' that must succeed together or fail together.
Unique: Implements transaction-like semantics for Xero operations within the MCP server, providing agents with all-or-nothing execution guarantees despite Xero's lack of native transaction support. Uses idempotency keys to enable safe retries.
vs alternatives: Safer than agents executing multi-step workflows independently because the server can coordinate rollback and prevent partial state changes.
Enables agents to traverse relationships between Xero entities (e.g., Invoice → Contact → Account) and automatically enrich responses with related data. The server implements lazy-loading or eager-loading strategies for related entities, reducing the number of API calls agents must make. For example, fetching an invoice can optionally include the associated contact details and account information in a single logical operation. Caches frequently accessed entities to reduce API calls.
Unique: Implements intelligent entity relationship traversal and caching within the MCP server, allowing agents to work with rich, interconnected Xero data without manually orchestrating multiple API calls.
vs alternatives: More efficient than agents making separate API calls for each entity because the server can batch requests and cache results, reducing latency and API call volume.
Provides agents with filtering, sorting, and pagination capabilities for Xero queries that return large result sets (e.g., listing all contacts or invoices). The server translates agent-friendly filter syntax (e.g., 'invoices where status=DRAFT and date > 2024-01-01') into Xero's Odata query language. Implements cursor-based pagination to efficiently traverse large datasets without loading all results into memory. Supports sorting by multiple fields and complex filter expressions.
Unique: Translates agent-friendly filter syntax into Xero's Odata query language, abstracting the complexity of Xero's query API from agents. Implements cursor-based pagination to efficiently handle large result sets.
vs alternatives: More efficient than agents fetching all results and filtering in-memory because the server pushes filtering/sorting to Xero's API, reducing data transfer and memory usage.
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 @xeroapi/xero-mcp-server at 21/100.
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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