| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 7 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes golang package information from pkg.go.dev through the Model Context Protocol (MCP) interface, enabling LLM agents and tools to query package metadata, documentation, and dependency information without direct HTTP calls. Implements MCP server protocol to translate pkg.go.dev REST API responses into structured tool calls that Claude and other MCP-compatible clients can invoke.
Unique: Bridges golang package documentation (pkg.go.dev) into the MCP ecosystem, allowing LLM agents to treat golang package lookup as a native tool call rather than requiring manual API integration or context injection
vs alternatives: Provides golang-specific package metadata access through MCP protocol, whereas generic web search or manual pkg.go.dev queries lack structured, tool-callable integration with LLM agents
Automatically generates MCP-compatible tool schemas that define how LLM clients can invoke golang package lookups, including parameter validation, return types, and documentation. Translates pkg.go.dev API capabilities into structured tool definitions that MCP clients (like Claude) can discover and invoke with proper type safety and argument validation.
Unique: Generates MCP tool schemas specifically for golang package queries, enabling type-safe function calling with pkg.go.dev data without requiring clients to manually define or validate query parameters
vs alternatives: Provides schema-driven golang package lookup vs. unstructured prompt-based queries or manual API integration, ensuring LLM agents can reliably invoke package lookups with validated inputs
Acts as a protocol bridge between MCP clients and the pkg.go.dev REST API, translating MCP tool calls into pkg.go.dev HTTP requests and marshaling responses back into structured MCP-compatible JSON. Handles authentication, request formatting, response parsing, and error handling to abstract away pkg.go.dev API details from LLM clients.
Unique: Implements MCP protocol translation layer specifically for pkg.go.dev, abstracting HTTP API complexity and enabling LLM agents to query golang packages through standardized MCP tool calls rather than direct REST integration
vs alternatives: Provides cleaner abstraction than embedding pkg.go.dev HTTP calls directly in agent prompts, and more maintainable than custom API wrappers by leveraging MCP's standardized tool protocol
Retrieves and exposes golang package dependency relationships from pkg.go.dev, allowing agents to traverse dependency trees and understand package relationships. Queries pkg.go.dev to extract direct and transitive dependencies, enabling analysis of dependency chains and impact assessment for package changes.
Unique: Exposes golang package dependency relationships through MCP, enabling LLM agents to programmatically traverse and analyze dependency graphs without manual pkg.go.dev navigation
vs alternatives: Provides structured dependency lookup vs. requiring agents to parse pkg.go.dev HTML or manually inspect go.mod files, enabling automated dependency analysis within agent workflows
Queries pkg.go.dev to retrieve version history, release dates, and changelog information for golang packages, enabling agents to track package evolution and identify stable vs. pre-release versions. Exposes version metadata including release timestamps, deprecation status, and version tags to support version selection and compatibility analysis.
Unique: Surfaces golang package version history and release metadata through MCP, allowing LLM agents to make informed version selection decisions based on release timelines and stability indicators
vs alternatives: Provides structured version history lookup vs. requiring agents to manually inspect pkg.go.dev or parse go.mod version constraints, enabling automated version compatibility analysis
Extracts golang package documentation (README, API docs, examples) from pkg.go.dev and renders it in a format suitable for LLM consumption. Parses pkg.go.dev documentation pages and converts them into structured text or markdown that agents can analyze, summarize, or use for code generation tasks.
Unique: Extracts and structures golang package documentation from pkg.go.dev for LLM consumption, enabling agents to access authoritative API documentation without manual navigation or context injection
vs alternatives: Provides structured documentation extraction vs. requiring agents to parse pkg.go.dev HTML or rely on stale documentation in training data, ensuring agents have current, accurate package information
Manages MCP server initialization, client connection handling, and protocol state management. Implements MCP server lifecycle including startup, client handshake, capability negotiation, and graceful shutdown, enabling reliable integration with MCP-compatible clients like Claude Desktop.
Unique: Implements MCP server protocol lifecycle management specifically for golang package queries, handling client connections and capability negotiation transparently
vs alternatives: Provides standardized MCP server lifecycle vs. custom protocol implementations, ensuring compatibility with existing MCP clients and infrastructure
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 godoc-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
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