{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-motherduck","slug":"motherduck","name":"MotherDuck","type":"mcp","url":"https://github.com/motherduckdb/mcp-server-motherduck","page_url":"https://unfragile.ai/motherduck","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-motherduck__cap_0","uri":"capability://data.processing.analysis.sql.query.execution.with.duckdb.dialect.support","name":"sql query execution with duckdb dialect support","description":"Executes arbitrary SQL queries against DuckDB or MotherDuck backends via the execute_query MCP tool, which parses SQL strings, routes them through a FastMCP-registered handler, and returns structured JSON results with configurable row/character limits to prevent resource exhaustion. The implementation abstracts over multiple database backends (in-memory, local files, S3, MotherDuck cloud) through a unified connection interface, allowing the same query execution path to work across heterogeneous data sources.","intents":["Run analytical SQL queries against local or cloud-hosted DuckDB databases from Claude or other AI assistants","Execute data transformations and aggregations without leaving the IDE or chat interface","Perform ad-hoc data exploration with result pagination and size limits"],"best_for":["Data analysts using Claude Desktop or Cursor IDE for exploratory analysis","AI agent developers building data-aware reasoning chains","Teams migrating from REST APIs to MCP for database access"],"limitations":["Results are truncated by --max-rows and --max-chars parameters; large result sets require pagination or filtering at query time","DuckDB dialect only — no support for PostgreSQL, MySQL, or other SQL dialects","Query execution is synchronous; long-running queries block the MCP connection","No built-in query optimization or cost estimation before execution"],"requires":["Python 3.9+","DuckDB 0.8.0+ or MotherDuck account with valid API token","MCP client (Claude Desktop, Cursor IDE, VS Code with MCP extension)","Network access to MotherDuck cloud (if using cloud backend)"],"input_types":["SQL query string (DuckDB dialect)","Optional database/schema context"],"output_types":["JSON object with result rows, column metadata, and execution stats","Error messages with SQL syntax or runtime details"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-motherduck__cap_1","uri":"capability://data.processing.analysis.database.schema.introspection.and.discovery","name":"database schema introspection and discovery","description":"Provides three complementary MCP tools (list_databases, list_tables, list_columns) that expose database metadata through structured queries against DuckDB's information_schema. These tools enable AI assistants to discover available databases, enumerate tables/views within a schema, and retrieve column definitions (name, type, nullable status) without requiring manual schema documentation. The implementation queries DuckDB's built-in metadata tables, making schema discovery work identically across all backend types (local, S3, MotherDuck).","intents":["Discover what databases and tables are available before writing queries","Inspect column names and types to generate syntactically correct SQL","Help AI assistants understand data structure for context-aware query generation"],"best_for":["AI agents that need to reason about database structure before query generation","Non-technical users exploring datasets through natural language","IDE integrations that provide autocomplete or schema hints"],"limitations":["Schema discovery is read-only; cannot detect schema changes in real-time if tables are modified by external processes","Column metadata is limited to name, type, and nullable status; no support for constraints, indexes, or custom metadata","MotherDuck shared databases may have visibility restrictions based on account permissions, but the tool does not expose permission errors clearly"],"requires":["Active database connection (local file, S3, or MotherDuck)","Read access to information_schema (standard in DuckDB)"],"input_types":["Optional database name (for list_tables)","Optional schema name (for list_tables and list_columns)","Table name (for list_columns)"],"output_types":["JSON array of database names","JSON array of table/view objects with names and types","JSON array of column objects with name, type, and nullable flag"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-motherduck__cap_2","uri":"capability://tool.use.integration.multi.backend.database.connection.management","name":"multi-backend database connection management","description":"Manages connections to four distinct database backend types (in-memory DuckDB, local .duckdb files, S3-hosted DuckDB files, MotherDuck cloud) through a unified connection abstraction in the database.py module. The server parses connection strings at startup (via --database flag or environment variables), maintains a connection pool, and exposes a switch_database_connection tool (when --allow-switch-databases flag is set) to change the active backend at runtime. Each backend has distinct security and performance characteristics: in-memory requires --read-write flag, local files support both persistent and ephemeral (lock-free) modes, S3 operates read-only with httpfs extension, and MotherDuck requires API token authentication.","intents":["Connect to local DuckDB files without managing separate database servers","Query data stored on S3 without downloading files locally","Use MotherDuck for shared, cloud-hosted analytics without infrastructure setup","Switch between multiple databases at runtime without restarting the server"],"best_for":["Solo developers prototyping data apps without database infrastructure","Teams using S3 as a data lake and needing SQL access without ETL","Organizations adopting MotherDuck for collaborative analytics","Developers building multi-tenant AI agents that query different databases per user"],"limitations":["In-memory databases are ephemeral; data is lost when the server restarts","Local file connections use DuckDB's file locking, which can cause contention in high-concurrency scenarios; ephemeral mode (--read-only) avoids locks but prevents writes","S3 connections are read-only and require the httpfs extension; writing to S3 is not supported","MotherDuck requires valid API token; token expiration or revocation is not automatically detected","Connection switching (--allow-switch-databases) is disabled by default for security; enabling it allows clients to change databases without authentication"],"requires":["Python 3.9+","DuckDB 0.8.0+","For local files: .duckdb file on accessible filesystem","For S3: AWS credentials (via environment variables or IAM role) and httpfs extension","For MotherDuck: MotherDuck account and API token (via MOTHERDUCK_TOKEN env var)","For in-memory: --read-write flag to enable write operations"],"input_types":["Connection string (format: :memory:, /path/to/file.duckdb, s3://bucket/file.duckdb, or motherduck://)","Optional database name for switch_database_connection tool"],"output_types":["Connection status confirmation","Error messages for invalid connection strings or authentication failures"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-motherduck__cap_3","uri":"capability://tool.use.integration.mcp.tool.registration.and.json.rpc.marshaling","name":"mcp tool registration and json-rpc marshaling","description":"Implements the Model Context Protocol specification using the FastMCP framework, which automatically registers five database tools (execute_query, list_databases, list_tables, list_columns, switch_database_connection) as JSON-RPC methods exposed over stdio or HTTP transport. The FastMCP framework handles schema validation, parameter marshaling, and error serialization, allowing MCP clients (Claude Desktop, Cursor IDE, VS Code) to invoke database operations as first-class tools without custom client-side code. Tool responses are automatically serialized to JSON with structured error handling.","intents":["Enable Claude and other AI assistants to invoke database operations as native tools","Provide a standardized interface for IDE integrations to access databases","Allow AI agents to compose database queries into multi-step reasoning chains"],"best_for":["AI assistant developers building Claude plugins or custom integrations","IDE extension developers adding database capabilities to Cursor or VS Code","Teams standardizing on MCP for tool integration across multiple AI systems"],"limitations":["FastMCP abstracts transport details, but debugging transport-level issues (stdio buffering, HTTP timeouts) requires understanding the underlying protocol","Tool schemas are defined in Python and automatically converted to JSON Schema; complex nested types may not serialize as expected","MCP clients must support the tool-calling protocol; older or non-standard clients cannot invoke tools"],"requires":["Python 3.9+","FastMCP framework (installed via pyproject.toml dependencies)","MCP client that supports tool calling (Claude 3.5+, Cursor IDE, VS Code with MCP extension)","For HTTP transport: --transport http flag and network connectivity"],"input_types":["Tool name and parameters (JSON-RPC format)","Optional transport configuration (stdio or HTTP)"],"output_types":["JSON-RPC response with tool result or error","Structured error messages with error codes and descriptions"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-motherduck__cap_4","uri":"capability://safety.moderation.result.pagination.and.resource.aware.output.limiting","name":"result pagination and resource-aware output limiting","description":"Implements configurable result truncation via --max-rows and --max-chars command-line flags, which are applied at the tool response layer to prevent resource exhaustion from large query results. When a query result exceeds these limits, the tool returns a partial result set with metadata indicating truncation, allowing clients to refine their queries (e.g., with LIMIT or WHERE clauses) to retrieve remaining data. This mechanism operates independently of query semantics, meaning the same query can return different result sizes depending on server configuration.","intents":["Prevent memory exhaustion when queries return millions of rows","Control bandwidth usage when streaming results over HTTP or slow connections","Force clients to write more specific queries by limiting exploratory result sizes"],"best_for":["Production deployments where resource limits are critical","Teams running shared MCP servers with multiple concurrent clients","Environments with strict bandwidth or memory constraints"],"limitations":["Truncation is applied after query execution, not before; expensive queries that produce large result sets still consume full database resources","Clients cannot easily determine how many rows were truncated; they must re-run queries with COUNT(*) to discover total result size","Character limit (--max-chars) is applied to the entire JSON response, including metadata; this can cause unexpected truncation if column names or types are very long"],"requires":["Command-line flags: --max-rows (default: 1000) and --max-chars (default: 1000000)","No additional dependencies"],"input_types":["Query result set (arbitrary size)","Configuration parameters (--max-rows, --max-chars)"],"output_types":["Truncated JSON result with partial row set","Metadata indicating whether truncation occurred"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-motherduck__cap_5","uri":"capability://tool.use.integration.motherduck.cloud.database.integration.with.token.authentication","name":"motherduck cloud database integration with token authentication","description":"Integrates with MotherDuck's cloud-hosted DuckDB service by accepting motherduck:// connection strings and authenticating via API tokens (provided via MOTHERDUCK_TOKEN environment variable). The server establishes a connection to MotherDuck's managed DuckDB instance, which allows querying shared databases and leveraging MotherDuck's compute infrastructure without local database files. The implementation treats MotherDuck as a first-class backend alongside local and S3 connections, exposing the same query execution and schema discovery tools.","intents":["Query shared datasets hosted on MotherDuck without downloading data locally","Collaborate with team members on shared MotherDuck databases through AI assistants","Leverage MotherDuck's managed infrastructure for analytics without running local DuckDB"],"best_for":["Teams using MotherDuck for collaborative analytics","Organizations with shared data warehouses on MotherDuck","Developers building AI agents that query MotherDuck databases"],"limitations":["Requires valid MotherDuck account and API token; token expiration is not automatically detected or refreshed","Network latency to MotherDuck cloud may be higher than local DuckDB queries","MotherDuck shared database visibility is controlled by account permissions; the server does not expose permission errors clearly","No support for MotherDuck-specific features like sharing or access control management through the MCP interface"],"requires":["MotherDuck account with valid API token","MOTHERDUCK_TOKEN environment variable set to API token","Network connectivity to MotherDuck cloud (motherduck.com)","DuckDB 0.8.0+ with MotherDuck extension support"],"input_types":["Connection string: motherduck://","API token (via environment variable)"],"output_types":["Query results from MotherDuck cloud database","Schema metadata from MotherDuck databases"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-motherduck__cap_6","uri":"capability://data.processing.analysis.s3.hosted.duckdb.file.querying.with.read.only.access","name":"s3-hosted duckdb file querying with read-only access","description":"Enables querying DuckDB files stored on S3 by attaching them via DuckDB's httpfs extension, which downloads files over HTTP and mounts them as read-only databases. The server accepts s3:// connection strings, automatically configures AWS credentials from environment variables or IAM roles, and enforces read-only access to prevent accidental data modification. This allows querying data lakes stored on S3 without downloading files locally or setting up separate database infrastructure.","intents":["Query data lake files on S3 without downloading them locally","Analyze datasets stored in S3 using SQL without ETL pipelines","Enable AI assistants to query S3-hosted data directly"],"best_for":["Data teams using S3 as a data lake","Organizations with large datasets that cannot fit in local storage","Developers building analytics agents that query S3 data"],"limitations":["Read-only access only; cannot write to S3-hosted DuckDB files","Requires httpfs extension, which must be installed and enabled in DuckDB","Network latency for downloading files from S3 may be significant for large databases","AWS credentials must be available via environment variables or IAM role; no support for temporary credentials or credential rotation"],"requires":["DuckDB 0.8.0+ with httpfs extension","S3 bucket with DuckDB files (.duckdb format)","AWS credentials (via AWS_ACCESS_KEY_ID/AWS_SECRET_ACCESS_KEY env vars or IAM role)","Network connectivity to S3"],"input_types":["Connection string: s3://bucket/path/to/file.duckdb","AWS credentials (via environment variables)"],"output_types":["Query results from S3-hosted DuckDB file","Schema metadata from S3 database"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-motherduck__cap_7","uri":"capability://automation.workflow.cli.configuration.and.transport.layer.abstraction","name":"cli configuration and transport layer abstraction","description":"Provides a command-line interface (via __init__.py entry point) that parses configuration flags (--database, --max-rows, --max-chars, --read-write, --allow-switch-databases, --transport) and initializes the MCP server with the appropriate transport layer (stdio or HTTP). The CLI abstracts transport details from the tool implementation, allowing the same database tools to work over both stdio (for Claude Desktop, Cursor IDE) and HTTP (for remote clients). Configuration is applied at startup and affects all subsequent tool invocations.","intents":["Configure database connection and resource limits without modifying code","Choose transport layer (stdio or HTTP) based on deployment environment","Enable/disable features (database switching, write access) for security"],"best_for":["DevOps engineers deploying MCP servers to production","Developers integrating MotherDuck into Claude Desktop or Cursor IDE","Teams running shared MCP servers with multiple clients"],"limitations":["Configuration is static at startup; changes require server restart","HTTP transport requires manual network configuration (port, TLS); no built-in reverse proxy or load balancing","CLI flags are not validated for semantic correctness (e.g., --max-rows 0 is accepted but may cause unexpected behavior)"],"requires":["Python 3.9+","Command-line access to run the server","For HTTP transport: network configuration and firewall rules"],"input_types":["Command-line flags and arguments"],"output_types":["Server startup confirmation","Configuration summary"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-motherduck__cap_8","uri":"capability://safety.moderation.error.handling.and.structured.error.responses","name":"error handling and structured error responses","description":"Implements error handling at multiple layers: SQL syntax errors from DuckDB are caught and returned as structured JSON-RPC error responses, connection errors (invalid credentials, unreachable backends) are reported with diagnostic messages, and resource exhaustion errors (query timeouts, memory limits) are surfaced to clients. The FastMCP framework automatically serializes exceptions to JSON-RPC error format, ensuring clients receive consistent error structures regardless of error source.","intents":["Diagnose SQL syntax errors and invalid queries","Identify connection issues (authentication, network, backend unavailability)","Understand resource exhaustion or timeout issues"],"best_for":["Developers debugging database queries through AI assistants","Teams monitoring MCP server health and reliability","Users troubleshooting connection issues"],"limitations":["Error messages are generic DuckDB errors; they may not be user-friendly for non-technical users","Connection errors do not distinguish between authentication failures, network timeouts, and backend unavailability","Query timeout errors do not indicate how long the query ran before timing out"],"requires":["No additional dependencies; error handling is built into FastMCP and DuckDB"],"input_types":["Any tool invocation that results in an error"],"output_types":["JSON-RPC error response with error code and message","Diagnostic information (e.g., SQL syntax error details)"],"categories":["safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":29,"verified":false,"data_access_risk":"high","permissions":["Python 3.9+","DuckDB 0.8.0+ or MotherDuck account with valid API token","MCP client (Claude Desktop, Cursor IDE, VS Code with MCP extension)","Network access to MotherDuck cloud (if using cloud backend)","Active database connection (local file, S3, or MotherDuck)","Read access to information_schema (standard in DuckDB)","DuckDB 0.8.0+","For local files: .duckdb file on accessible filesystem","For S3: AWS credentials (via environment variables or IAM role) and httpfs extension","For MotherDuck: MotherDuck account and API token (via MOTHERDUCK_TOKEN env var)"],"failure_modes":["Results are truncated by --max-rows and --max-chars parameters; large result sets require pagination or filtering at query time","DuckDB dialect only — no support for PostgreSQL, MySQL, or other SQL dialects","Query execution is synchronous; long-running queries block the MCP connection","No built-in query optimization or cost estimation before execution","Schema discovery is read-only; cannot detect schema changes in real-time if tables are modified by external processes","Column metadata is limited to name, type, and nullable status; no support for constraints, indexes, or custom metadata","MotherDuck shared databases may have visibility restrictions based on account permissions, but the tool does not expose permission errors clearly","In-memory databases are ephemeral; data is lost when the server restarts","Local file connections use DuckDB's file locking, which can cause contention in high-concurrency scenarios; ephemeral mode (--read-only) avoids locks but prevents writes","S3 connections are read-only and require the httpfs extension; writing to S3 is not supported","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.28,"ecosystem":0.3,"match_graph":0.25,"freshness":0.9,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:20.443Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=motherduck","compare_url":"https://unfragile.ai/compare?artifact=motherduck"}},"signature":"H0sWbgw2+K9hNc83s3GCGykbLNG+6b9h+S63O5WQ0P+WQpwJi53HOg3zEm1TA999nq5SVAjt38GdQaMaLaTkAA==","signedAt":"2026-06-17T02:37:05.697Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/motherduck","artifact":"https://unfragile.ai/motherduck","verify":"https://unfragile.ai/api/v1/verify?slug=motherduck","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}