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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 7 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Implements MCP server protocol to expose Atlan's metadata catalog as a standardized tool interface that LLM agents can query and reference. Uses the Model Context Protocol to establish bidirectional communication between AI tools (Claude, etc.) and Atlan's metadata platform, allowing agents to retrieve business context, data lineage, and asset relationships without custom API integration code. Metadata is injected into the agent's context window as structured tool definitions that the LLM can invoke during reasoning.
Unique: Implements MCP server pattern specifically for metadata platforms, allowing LLMs to treat Atlan's catalog as a native tool rather than requiring custom API clients. Uses Atlan's existing metadata graph and lineage engine as the backing data source, avoiding duplication and ensuring consistency with the source of truth.
vs alternatives: Tighter integration than generic REST API wrappers because it leverages MCP's standardized tool schema format, making metadata queryable by any MCP-compatible LLM without custom prompt engineering or function-calling boilerplate.
Exposes Atlan's lineage graph as queryable tools that agents can use to understand upstream/downstream data dependencies and transformation chains. The MCP server translates lineage queries into Atlan API calls, returning structured parent-child relationships, transformation logic, and impact analysis. Agents can traverse lineage paths to answer questions like 'what data feeds into this dashboard' or 'what will break if we change this table schema'.
Unique: Wraps Atlan's lineage graph engine as MCP tools, allowing agents to perform multi-hop traversals and impact analysis without writing SQL or custom graph queries. Leverages Atlan's pre-computed lineage indices for fast traversal rather than computing lineage on-the-fly.
vs alternatives: More efficient than agents querying raw data catalogs because it exposes pre-computed lineage relationships as first-class tools, avoiding the need for agents to reconstruct lineage from metadata fields or execute complex graph algorithms.
Provides MCP tools to query Atlan's business glossary, classifications, and custom metadata attributes, allowing agents to understand business context and governance policies. Agents can look up term definitions, ownership information, data quality rules, and classification tags to enrich their reasoning. The server translates glossary queries into Atlan API calls and returns structured metadata that agents can incorporate into responses or decision-making logic.
Unique: Exposes Atlan's business metadata layer (glossaries, classifications, custom attributes) as queryable MCP tools, treating business context as first-class information that agents can reference during reasoning. Integrates with Atlan's metadata model rather than requiring separate glossary systems.
vs alternatives: More authoritative than agents relying on training data or external glossaries because it queries the live business glossary in Atlan, ensuring agents always reference the current, organization-approved definitions and governance policies.
Implements MCP tools for searching Atlan's asset catalog using both structured filters (asset type, owner, classification) and semantic search capabilities. The server translates search queries into Atlan API calls, supporting full-text search, faceted filtering, and potentially semantic embeddings if Atlan has indexed assets. Agents can discover relevant data assets, users, and metadata without knowing exact asset names, enabling exploratory data discovery workflows.
Unique: Wraps Atlan's search and discovery APIs as MCP tools, allowing agents to perform exploratory searches without requiring users to know asset names or exact metadata. Combines structured filtering with full-text and potentially semantic search in a single tool interface.
vs alternatives: More discoverable than agents relying on exact asset names because it supports fuzzy matching and semantic search, enabling agents to find relevant assets even when users provide vague or business-language descriptions rather than technical identifiers.
Provides MCP tools to fetch detailed metadata for specific assets (tables, dashboards, models, etc.) from Atlan, including schema information, ownership, quality metrics, and custom attributes. Agents can retrieve comprehensive asset profiles to answer detailed questions or validate assumptions before recommending data usage. The server handles asset lookups by qualified name, GUID, or search results, returning structured metadata that agents can parse and reason about.
Unique: Exposes Atlan's asset metadata APIs as MCP tools, allowing agents to fetch comprehensive asset profiles including schema, quality, and custom attributes in a single structured query. Integrates with Atlan's metadata model to ensure consistency with the source of truth.
vs alternatives: More comprehensive than agents querying individual metadata fields because it returns full asset profiles with schema, quality, and custom attributes in structured format, reducing the number of queries agents need to make and improving reasoning accuracy.
Implements the Model Context Protocol (MCP) server specification, enabling the Atlan toolkit to work with any MCP-compatible client including Claude Desktop, VS Code extensions, and custom MCP clients. The server handles MCP protocol negotiation, tool schema definition, and request/response serialization. Supports both stdio and HTTP transport mechanisms for flexible deployment options (local, containerized, or cloud-hosted).
Unique: Implements full MCP server specification with support for multiple transport mechanisms (stdio, HTTP), enabling flexible deployment from local development to cloud-hosted production environments. Abstracts Atlan API complexity behind standardized MCP tool schemas.
vs alternatives: More flexible than custom API wrappers because it uses the standardized MCP protocol, allowing the same server to work with any MCP-compatible client without client-specific code or configuration.
Implements MCP-level access control that validates agent operations against Atlan's role-based access control (RBAC) and attribute-based access control (ABAC) policies. Enforces permissions at the tool invocation level, ensuring agents can only access metadata and perform operations that their API credentials permit, with detailed permission validation results that agents can use to handle access denied scenarios gracefully.
Unique: Enforces Atlan's access control policies at MCP tool invocation level, preventing agents from accessing restricted metadata even if misconfigured; integrates with Atlan's audit system to provide complete traceability of agent operations
vs alternatives: Unlike agents that implement access control logic themselves, Atlan's MCP server enforces policies server-side, ensuring consistent policy application and preventing accidental policy bypass through agent misconfiguration
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 Atlan 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
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