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| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Retrieves Bing search analytics data through the Bing Webmaster Tools API, exposing query performance metrics (impressions, clicks, CTR, position) with filtering by date range, query type, and device category. Implements MCP resource protocol to expose analytics as queryable endpoints, translating HTTP REST calls into structured JSON responses that map directly to Bing's analytics schema.
Unique: Exposes Bing's proprietary search analytics through MCP protocol, enabling LLM agents and automation tools to query search performance without building custom REST clients; translates Bing's analytics schema into standardized MCP resource format
vs alternatives: Provides direct Bing search data access (not available through Google Search Console MCP servers) and integrates natively with MCP-based agent frameworks, eliminating the need for separate API wrapper libraries
Monitors the indexing status of URLs in a domain through Bing Webmaster Tools, retrieving page-level indexing state (indexed, blocked, error) and crawl diagnostics. Implements polling-style status checks via MCP tools that call Bing's indexing status endpoints, returning structured metadata about why pages may be blocked or failing to index.
Unique: Provides programmatic access to Bing's page-level indexing diagnostics through MCP, enabling automated monitoring of crawl errors and indexation blocks without manual Webmaster Tools dashboard checks; integrates diagnostic reasons into structured responses
vs alternatives: Offers Bing-specific indexing insights (Google Search Console doesn't expose equivalent diagnostic detail through public APIs) and enables real-time monitoring integration with LLM agents for autonomous site health management
Submits URLs to Bing's index queue through the Bing Webmaster Tools API, triggering crawl requests for new or updated pages. Implements batch submission logic that groups URLs and sends them via Bing's URL submission endpoint, handling rate limiting and returning submission status for each URL. Supports both individual URL submissions and bulk batch operations.
Unique: Wraps Bing's URL submission API in MCP tool format, enabling LLM agents and automation frameworks to request crawls programmatically; implements batch grouping logic to respect Bing's daily submission quotas and handles submission status tracking
vs alternatives: Integrates Bing URL submission directly into MCP agent workflows (unlike manual dashboard submission or generic HTTP clients), enabling autonomous content publishing pipelines that automatically notify Bing of new pages
Retrieves SEO insights and keyword recommendations from Bing Webmaster Tools, including suggested keywords for content optimization, search intent analysis, and competitive keyword data. Calls Bing's insights endpoints to surface keyword opportunities and content gaps, returning structured recommendations that map to query volume and competition metrics.
Unique: Exposes Bing's proprietary keyword recommendation engine through MCP, providing SEO insights based on Bing's index and user behavior; integrates search intent classification and competition scoring directly into structured responses
vs alternatives: Offers Bing-native keyword insights (complementary to Google Search Console data) and enables integration with LLM-powered content planning agents that can autonomously identify and prioritize content opportunities
Manages site-level configuration in Bing Webmaster Tools, including preferred domain format (www vs non-www), crawl rate settings, and robots.txt management. Implements CRUD operations via MCP tools that call Bing's site settings endpoints, allowing programmatic updates to crawl preferences and domain configuration without manual dashboard access.
Unique: Provides programmatic site configuration management through MCP, enabling automation of domain migrations and crawl rate adjustments without manual Webmaster Tools dashboard interaction; validates configuration changes before submission
vs alternatives: Integrates site settings management directly into automation workflows and LLM agents, enabling autonomous handling of domain configuration changes during migrations or infrastructure updates
Exposes Bing Webmaster Tools data and operations as MCP resources and tools, enabling any MCP-compatible client (Claude, LLM agents, automation frameworks) to interact with Bing data natively. Implements MCP server protocol with resource endpoints for analytics, status checks, and tool definitions for submissions and configuration changes, translating between MCP's standardized format and Bing's REST API.
Unique: Implements full MCP server protocol for Bing Webmaster Tools, standardizing Bing's REST API into MCP's tool and resource format; enables seamless integration with any MCP-compatible client without custom API wrapper code
vs alternatives: Provides MCP-native Bing integration (unlike raw REST API clients or generic HTTP wrappers), enabling LLM agents and automation frameworks to use Bing data with the same interface as other MCP tools
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 Bing Webmaster Tools 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
+1 more capabilities