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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Queries the Maven Central Repository API to retrieve the latest version information, metadata, and availability status for Java/JVM dependencies. Implements HTTP-based polling against Maven Central's REST endpoints to fetch current artifact metadata including version numbers, release dates, and dependency coordinates without requiring local repository caches or index files.
Unique: Exposes Maven Central Repository queries as an MCP tool callable from Claude, enabling LLM-assisted dependency selection with real-time accuracy rather than relying on training data cutoffs or static dependency databases
vs alternatives: Provides live Maven Central data directly within Claude conversations, whereas traditional Maven plugins require local CLI invocation and IDE integration requires separate tooling setup
Analyzes Maven version strings and constraints (e.g., '[1.0,2.0)', '1.2.3-SNAPSHOT') to determine which available versions satisfy specified ranges. Implements semantic versioning parsing and range matching logic to help developers understand version compatibility without manual trial-and-error or consulting Maven documentation.
Unique: Integrates Maven's version range syntax parsing directly into Claude's context, allowing natural-language discussion of version constraints with immediate validation rather than requiring developers to manually test ranges locally
vs alternatives: Simpler and more accessible than running `mvn dependency:tree` or consulting Maven's version range documentation, with results available inline in the conversation
Aggregates Maven Central metadata (POM files, artifact descriptions, maintainer information, license data) and synthesizes it into structured dependency profiles. Parses POM XML to extract transitive dependencies, build properties, and plugin configurations, presenting this information in a format suitable for LLM-assisted decision-making about dependency selection and integration.
Unique: Extracts and synthesizes POM metadata into LLM-friendly structured formats, enabling Claude to reason about dependency implications without requiring developers to manually inspect XML or run Maven commands
vs alternatives: More accessible than parsing POM files manually or using Maven's dependency plugin, with results formatted for natural-language discussion rather than CLI output
Implements keyword-based and metadata-based search against Maven Central's artifact index to discover libraries matching developer-provided search terms. Uses Maven Central's search API to return ranked results with artifact coordinates, descriptions, and popularity metrics, enabling exploratory dependency discovery within Claude conversations.
Unique: Brings Maven Central's search capability into Claude's conversational context, allowing developers to discover and evaluate libraries through natural-language queries rather than navigating the Maven Central web UI
vs alternatives: More conversational and integrated than visiting Maven Central's website or using IDE search plugins, with results available for immediate discussion and evaluation
Identifies available updates for declared dependencies and retrieves associated changelog or release note information from Maven Central and linked repositories. Compares current versions against available versions, flags security updates or major version changes, and synthesizes release information to help developers make informed upgrade decisions.
Unique: Synthesizes version history and changelog data into Claude-friendly upgrade recommendations, enabling LLM-assisted decision-making about when and how to upgrade dependencies based on actual release information
vs alternatives: More intelligent than simple version comparison tools, providing context about what changed and why an upgrade might be beneficial or risky
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 Maven at 20/100.
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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