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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 7 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Executes Apple's xctrace command-line tool through an MCP server interface, enabling remote or programmatic invocation of Xcode's performance profiling capabilities. The MCP server wraps xctrace subprocess execution, marshaling arguments and capturing structured profiling output (CPU, memory, disk I/O traces) that can be consumed by LLM agents or automation workflows without direct Xcode GUI interaction.
Unique: Provides MCP-native wrapping of xctrace with subprocess lifecycle management, allowing LLM agents and automation tools to trigger Apple's native profiling without Xcode GUI or direct shell access
vs alternatives: Enables headless xctrace execution in CI/CD and agent workflows where Xcode.app is unavailable, unlike GUI-only profiling tools
Wraps Apple's xcrun utility through MCP, enabling execution of arbitrary Xcode-provided tools (simulators, compilers, code signing, etc.) with isolated environment variables and working directory context. The server marshals xcrun subprocess calls, capturing stdout/stderr and exit codes, allowing remote agents to invoke simulator management, device queries, and build tool chains without direct shell access.
Unique: Provides MCP-native subprocess wrapping of xcrun with explicit environment isolation and exit code capture, enabling safe remote invocation of Xcode toolchain without shell injection risks
vs alternatives: Safer and more composable than raw shell execution for Xcode tools; integrates directly with MCP-aware agents and CI/CD systems without requiring SSH or shell scripting
Executes xcodebuild commands through MCP to compile iOS/macOS projects, run unit/UI tests, and generate build artifacts. The server marshals xcodebuild subprocess invocation with scheme/target selection, build configuration (Debug/Release), and test filtering, capturing build logs and test results in structured formats (JSON, XML) for downstream analysis.
Unique: Provides MCP-native orchestration of xcodebuild with structured result capture (JSON/XML test results, artifact paths), enabling LLM agents and CI systems to parse and act on build/test outcomes without log parsing
vs alternatives: Integrates xcodebuild into MCP-aware workflows with structured output, unlike raw shell invocation; enables agent-driven test analysis and failure remediation
Manages iOS/macOS simulator lifecycle (launch, shutdown, reset, device list queries) through MCP by wrapping xcrun simctl commands. The server provides structured queries of available simulators, their runtime versions, and device states, enabling remote agents to provision and manage simulator environments for testing without GUI interaction.
Unique: Provides MCP-native wrapping of xcrun simctl with structured device enumeration and state queries, enabling agents to discover and manage simulator environments without parsing raw simctl output
vs alternatives: Integrates simulator management into MCP workflows with structured queries, unlike shell scripts that require fragile output parsing
Captures and parses xcodebuild output in real-time, converting unstructured build logs into structured events (compilation errors, warnings, test results) that can be consumed by agents. The server may implement log line parsing using regex or state machines to extract compiler diagnostics, test outcomes, and build phase transitions, enabling downstream analysis without manual log inspection.
Unique: Provides structured event extraction from xcodebuild logs via regex/state machine parsing, converting unstructured text into actionable diagnostics (file, line, severity) for agent consumption
vs alternatives: Enables agents to act on build failures without manual log inspection; more reliable than raw log parsing because it normalizes Xcode version differences
Wraps code signing and provisioning profile operations (xcrun security, codesign, provisioning profile queries) through MCP, enabling remote agents to manage signing identities, validate certificates, and query provisioning profiles. The server may parse provisioning profile metadata (entitlements, team ID, expiration) and provide structured queries for certificate validation.
Unique: Provides MCP-native wrapping of code signing tools with structured provisioning profile metadata extraction, enabling agents to validate signing prerequisites before build/deployment
vs alternatives: Integrates code signing validation into MCP workflows with structured queries, unlike manual certificate/profile inspection
Queries connected iOS/macOS devices and available simulators with their runtime versions, architectures, and capabilities through MCP. The server wraps xcrun commands (xcrun xctrace list devices, simctl list) and parses output to provide structured device inventories, enabling agents to select appropriate targets for testing or profiling based on OS version and device type.
Unique: Provides MCP-native device/simulator discovery with structured runtime version and capability queries, enabling agents to make informed target selection without manual device inspection
vs alternatives: Integrates device discovery into MCP workflows with structured queries, unlike shell scripts that require fragile output parsing
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 xctools 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
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