| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 8 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes Microsoft 365 services (Teams, SharePoint, OneDrive, Outlook, etc.) as MCP tools that Claude and other LLM clients can invoke through standardized tool-calling interfaces. Implements the Model Context Protocol specification to translate M365 REST API calls into LLM-compatible function schemas with automatic authentication handling via Microsoft Graph API credentials.
Unique: First-party MCP server from Microsoft that natively bridges Claude/LLM tool-calling to Microsoft Graph API with built-in tenant-aware authentication, eliminating the need for custom OAuth wrappers or API gateway layers
vs alternatives: Tighter integration than third-party MCP servers because it's maintained by Microsoft and can leverage internal Graph API optimization paths; simpler than building custom Copilot plugins because MCP standardizes the interface
Manages OAuth 2.0 token lifecycle and Microsoft Graph API permission scopes at the tenant level, automatically handling token refresh, scope validation, and delegated vs. application permissions. Implements Azure AD authentication patterns to ensure that LLM-invoked M365 operations respect the authenticated user's permissions and organizational policies without exposing credentials to the LLM client.
Unique: Implements Microsoft-specific OAuth patterns (incremental consent, multi-tenant support, managed identity integration) rather than generic OAuth, enabling seamless integration with Azure AD conditional access policies and M365 compliance frameworks
vs alternatives: More secure than generic API key management because it leverages Azure AD's token lifecycle and conditional access; more flexible than static API keys because it supports per-user permission scoping and audit logging
Enables Claude and other LLMs to query Teams conversations using natural language or structured filters, returning message threads with metadata (sender, timestamp, channel context). Translates LLM search intents into Microsoft Graph API queries against the Teams service, handling pagination and result ranking to surface relevant conversations within token budgets.
Unique: Integrates Teams search via MCP protocol, allowing LLMs to query conversation history without custom Teams SDK integration; leverages Microsoft Graph's native Teams search capabilities rather than building a separate indexing layer
vs alternatives: More current than RAG-based approaches because it queries live Teams data rather than static embeddings; simpler than building custom Teams bot because it uses standard MCP tool-calling instead of Teams-specific webhooks
Allows Claude and other LLMs to search SharePoint sites and document libraries using natural language, returning file metadata, content previews, and download URLs. Implements Microsoft Graph Sites API queries with support for filtering by site, library, document type, and metadata properties, enabling AI agents to locate and surface relevant documents without manual navigation.
Unique: Exposes SharePoint search through MCP tool-calling, enabling LLMs to query document libraries without building custom SharePoint search connectors; integrates with Microsoft Graph Sites API for tenant-wide document discovery
vs alternatives: More comprehensive than site-specific search because it can query across multiple SharePoint sites in a single request; simpler than Azure Search integration because it uses native Graph API without additional indexing infrastructure
Enables Claude and other LLMs to draft, format, and send emails on behalf of authenticated users through MCP tool calls. Implements email composition with support for recipients, subject, body formatting, attachments, and scheduling, translating LLM-generated email content into Microsoft Graph Mail API calls while respecting user permissions and organizational email policies.
Unique: Provides MCP-based email composition and sending, allowing LLMs to generate and dispatch emails without custom Outlook SDK integration; supports scheduled send and attachment linking via Microsoft Graph Mail API
vs alternatives: More secure than email forwarding because it uses OAuth-authenticated Graph API calls rather than SMTP credentials; more flexible than email templates because LLMs can generate dynamic content based on context
Enables Claude and other LLMs to list, read, and retrieve files from OneDrive using MCP tool calls, supporting file metadata queries, content preview generation, and file download URLs. Implements Microsoft Graph Drive API operations with support for folder navigation, file filtering, and content extraction to provide LLMs with access to user files for analysis and context.
Unique: Exposes OneDrive file operations through MCP protocol, allowing LLMs to access user files without custom OneDrive SDK or file upload workflows; integrates with Microsoft Graph Drive API for seamless file retrieval and content extraction
vs alternatives: More convenient than manual file uploads because it accesses files in-place; more secure than sharing file contents via chat because it uses OAuth-authenticated Graph API calls
Enables Claude and other LLMs to create, read, and modify calendar events in Outlook using MCP tool calls. Implements calendar operations with support for event details (title, time, attendees, location), recurring patterns, and attendee management, translating LLM-generated scheduling requests into Microsoft Graph Calendar API calls while handling timezone conversion and conflict detection.
Unique: Provides MCP-based calendar operations, allowing LLMs to schedule meetings without custom Outlook SDK integration; supports attendee management and recurring events via Microsoft Graph Calendar API
vs alternatives: More flexible than email-based scheduling because it directly modifies calendar state; more integrated than external scheduling tools because it uses native Outlook calendar API
Implements the Model Context Protocol (MCP) server specification, exposing M365 capabilities as standardized LLM tools with JSON Schema definitions. Handles MCP request/response serialization, tool discovery, parameter validation, and error handling, enabling any MCP-compatible LLM client (Claude, custom agents) to invoke M365 operations through a unified interface without client-specific integration code.
Unique: Implements MCP server specification for M365, providing standardized tool-calling interface that works with any MCP-compatible LLM client; uses JSON Schema for tool parameter validation and discovery
vs alternatives: More standardized than custom API wrappers because it follows MCP specification; more flexible than SDK-specific implementations because it supports multiple LLM clients
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 @microsoft/workiq at 24/100. @microsoft/workiq leads on ecosystem, while Supabase is stronger on quality.
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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