{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-singlestore","slug":"singlestore","name":"SingleStore","type":"mcp","url":"https://github.com/singlestore-labs/mcp-server-singlestore","page_url":"https://unfragile.ai/singlestore","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-singlestore__cap_0","uri":"capability://tool.use.integration.mcp.native.sql.query.execution.on.singlestore.workspaces","name":"mcp-native sql query execution on singlestore workspaces","description":"Executes arbitrary SQL queries against SingleStore database workspaces through the Model Context Protocol, translating natural language requests from LLM clients into parameterized SQL execution via the SingleStore Management API. The server handles connection pooling, query result formatting, and error translation back to the LLM client without requiring direct database credentials in the LLM context.","intents":["I want Claude to run SQL queries against my SingleStore database and interpret results","I need to let an LLM agent perform analytics queries on my workspace without exposing connection strings","I want to execute DDL/DML operations through natural language without writing SQL directly"],"best_for":["LLM application developers building database-aware agents","Data analysts using Claude Desktop or Cursor IDE for exploratory queries","Teams automating database operations through natural language interfaces"],"limitations":["Query execution is synchronous — long-running queries may timeout depending on MCP client timeout settings","No built-in query result pagination — large result sets are returned in full, potentially exceeding context windows","Query results are formatted as plain text/JSON, not streamed, so memory usage scales with result size","No query optimization hints or execution plan analysis provided to the LLM"],"requires":["Python 3.11+","Valid SingleStore Management API credentials (API key or OAuth token)","Active SingleStore workspace with network access from MCP server","MCP-compatible LLM client (Claude Desktop, Cursor IDE, or compatible)"],"input_types":["natural language query description","workspace identifier (string)","optional SQL query string"],"output_types":["structured query results (JSON/text)","error messages with SQL diagnostics","execution metadata (rows affected, query time)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_1","uri":"capability://automation.workflow.virtual.workspace.provisioning.and.lifecycle.management","name":"virtual workspace provisioning and lifecycle management","description":"Creates and manages ephemeral SingleStore virtual workspaces through MCP tools, enabling LLM agents to spin up isolated database environments on-demand. The server translates workspace creation requests into SingleStore Management API calls, handling configuration parameters, resource allocation, and returning connection metadata back to the LLM client for subsequent operations.","intents":["I want to create a temporary database environment for testing without manual setup","I need the LLM to provision isolated workspaces for different projects or experiments","I want to automate workspace lifecycle (create, configure, teardown) through natural language"],"best_for":["Development teams using LLM agents for infrastructure automation","Data scientists provisioning ephemeral environments for experiments","Multi-tenant SaaS applications automating workspace creation per customer"],"limitations":["Workspace creation is asynchronous but MCP tool returns immediately — LLM must poll for readiness status","No built-in cost controls — runaway workspace creation could incur unexpected charges","Workspace deletion is permanent and non-recoverable through this interface","Resource sizing is limited to SingleStore's predefined workspace tiers, no custom resource allocation"],"requires":["Python 3.11+","SingleStore Management API credentials with workspace creation permissions","Active SingleStore organization with available workspace quota","MCP client with tool-calling capability"],"input_types":["workspace name (string)","workspace tier/size specification","optional configuration parameters (region, backup settings)"],"output_types":["workspace metadata (ID, connection endpoint, status)","provisioning status and estimated readiness time","error details if creation fails"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_10","uri":"capability://safety.moderation.error.translation.and.diagnostic.response.formatting","name":"error translation and diagnostic response formatting","description":"Translates SingleStore API errors and database errors into human-readable MCP responses, providing diagnostic information to LLM clients without exposing raw API details. The server catches API exceptions, formats error messages with context, and returns structured error responses that enable LLM clients to understand and potentially recover from failures.","intents":["I want Claude to understand why a query failed and suggest fixes","I need clear error messages from the MCP server instead of raw API errors","I want the LLM to handle errors gracefully and retry with different parameters"],"best_for":["LLM agents implementing error recovery and retry logic","Development teams debugging MCP integration issues","Users getting clear error messages from LLM-driven database operations"],"limitations":["Error translation is basic — complex API errors may not map to meaningful messages","No error categorization — LLM clients cannot distinguish between transient and permanent failures","Diagnostic information is limited to error message text — no structured error codes","Error context is lost if errors occur in nested API calls"],"requires":["Python 3.11+","MCP server running with error handling enabled"],"input_types":["API exceptions from SingleStore Management API","database query errors","authentication failures"],"output_types":["human-readable error messages","diagnostic context (query, workspace, operation)","suggested remediation steps (if applicable)"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_2","uri":"capability://automation.workflow.notebook.creation.and.execution.scheduling","name":"notebook creation and execution scheduling","description":"Enables LLM clients to create SingleStore Spaces notebooks and schedule their execution as jobs through MCP tools. The server translates notebook creation requests into SingleStore Management API calls, manages notebook content storage, and sets up job scheduling with cron-like scheduling expressions for automated execution.","intents":["I want Claude to create and schedule recurring data analysis notebooks","I need to automate notebook execution on a schedule without manual intervention","I want the LLM to generate notebook code and immediately schedule it for execution"],"best_for":["Data teams automating recurring analysis and reporting workflows","LLM agents building self-modifying analysis pipelines","Organizations centralizing notebook management through natural language interfaces"],"limitations":["Notebook content is limited to SingleStore Spaces format — no arbitrary code execution","Job scheduling uses SingleStore's scheduler, not external cron systems — limited to SingleStore's scheduling capabilities","No built-in notebook versioning or rollback — overwrites are permanent","Job execution results are stored in SingleStore, not streamed back to LLM in real-time"],"requires":["Python 3.11+","SingleStore Management API credentials with notebook creation permissions","Active SingleStore workspace for notebook execution","Valid cron expression or scheduling parameters"],"input_types":["notebook name and description (string)","notebook content/code (SQL or Python)","scheduling expression (cron format or frequency)","workspace target for execution"],"output_types":["notebook metadata (ID, creation timestamp)","job scheduling confirmation","job execution history and status","execution logs and results"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_3","uri":"capability://search.retrieval.organization.and.workspace.metadata.retrieval","name":"organization and workspace metadata retrieval","description":"Retrieves hierarchical organizational metadata including workspace groups, individual workspaces, and regional availability through MCP tools that query the SingleStore Management API. The server caches and structures this metadata to provide LLM clients with complete visibility into available resources, enabling intelligent workspace selection and organization-aware operations.","intents":["I want Claude to list all available workspaces in my organization","I need the LLM to understand my organization structure to make informed workspace selection","I want to query available regions and workspace groups for deployment decisions"],"best_for":["Multi-workspace organizations needing LLM-driven resource discovery","Teams automating workspace selection based on organizational structure","DevOps engineers building LLM agents for infrastructure management"],"limitations":["Metadata is retrieved on-demand with no built-in caching — repeated queries incur API calls","Workspace metadata does not include real-time resource utilization or cost data","Regional availability is static and may not reflect dynamic capacity constraints","No filtering or search capabilities — returns full organizational hierarchy regardless of relevance"],"requires":["Python 3.11+","SingleStore Management API credentials with read permissions","Active SingleStore organization","MCP client with tool-calling capability"],"input_types":["optional organization ID or workspace group filter"],"output_types":["structured organization metadata (JSON)","workspace list with IDs, names, and status","workspace group hierarchy","available regions and their properties"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_4","uri":"capability://safety.moderation.oauth.based.browser.authentication.with.token.management","name":"oauth-based browser authentication with token management","description":"Implements OAuth 2.0 authentication flow through browser-based login, handling token acquisition, refresh, and storage without exposing credentials in LLM context. The server manages the OAuth provider integration, handles token lifecycle (expiration, refresh), and provides secure credential management through SingleStore's OAuth endpoints.","intents":["I want to authenticate with SingleStore without storing API keys in configuration files","I need secure OAuth token management that refreshes automatically","I want to use browser-based login for interactive MCP client setup"],"best_for":["Desktop LLM clients (Claude Desktop, Cursor) requiring interactive authentication","Development environments where API key management is cumbersome","Organizations with OAuth-based identity management requirements"],"limitations":["Browser authentication requires interactive user participation — not suitable for headless/server deployments","Token refresh is automatic but requires network connectivity to SingleStore OAuth endpoints","Token storage is local to the MCP server instance — not shared across multiple clients","OAuth token expiration handling may cause intermittent failures if refresh fails silently"],"requires":["Python 3.11+","Web browser access for OAuth flow","Network connectivity to SingleStore OAuth provider","MCP client running on same machine or with local network access"],"input_types":["user browser interaction (OAuth consent)","optional organization/workspace context"],"output_types":["OAuth access token (stored locally, not exposed to LLM)","token expiration metadata","authentication status confirmation"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_5","uri":"capability://search.retrieval.job.execution.monitoring.and.history.retrieval","name":"job execution monitoring and history retrieval","description":"Retrieves execution history, status, and logs for scheduled jobs through MCP tools that query the SingleStore Management API. The server provides job details including execution timestamps, status (success/failure), and execution logs, enabling LLM clients to monitor and troubleshoot automated workflows.","intents":["I want Claude to check the status of scheduled notebook jobs","I need to retrieve execution logs for failed jobs to understand what went wrong","I want the LLM to monitor job execution history and alert on failures"],"best_for":["Data teams monitoring automated notebook execution","LLM agents implementing self-healing workflows with failure detection","Operations teams using LLM clients for job monitoring dashboards"],"limitations":["Job history is limited to SingleStore's retention policy — old execution records may be purged","Execution logs are retrieved as bulk text, not streamed — large logs may exceed context limits","No real-time job execution monitoring — polling is required for live status updates","Job filtering is limited to job ID and workspace — no advanced query capabilities"],"requires":["Python 3.11+","SingleStore Management API credentials with read permissions","Valid job ID or workspace context","MCP client with tool-calling capability"],"input_types":["job ID (string)","optional workspace filter","optional date range for history queries"],"output_types":["job metadata (ID, name, schedule, status)","execution history with timestamps and status","execution logs and error messages","performance metrics (execution time, rows processed)"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_6","uri":"capability://search.retrieval.notebook.sample.discovery.and.template.retrieval","name":"notebook sample discovery and template retrieval","description":"Lists available SingleStore notebook samples and templates through MCP tools, enabling LLM clients to discover pre-built analysis patterns and use them as starting points. The server queries SingleStore's sample library and returns structured metadata including notebook descriptions, required datasets, and execution requirements.","intents":["I want Claude to discover available notebook templates for common analysis patterns","I need the LLM to recommend relevant notebook samples based on my data","I want to use pre-built notebooks as starting points for custom analysis"],"best_for":["Data analysts discovering analysis patterns through LLM recommendations","Teams standardizing on pre-built notebook templates","LLM agents building analysis workflows from template libraries"],"limitations":["Sample library is static and managed by SingleStore — no custom sample registration","Sample metadata may not include detailed execution requirements or dependencies","Samples are read-only discovery tools — actual notebook creation requires separate tool","No sample search or filtering by category — full library is returned regardless of relevance"],"requires":["Python 3.11+","SingleStore Management API credentials with read permissions","MCP client with tool-calling capability"],"input_types":["optional category or keyword filter (if supported)"],"output_types":["list of notebook samples with metadata","sample descriptions and use cases","required datasets and dependencies","sample code snippets"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_7","uri":"capability://search.retrieval.personal.file.and.workspace.resource.management","name":"personal file and workspace resource management","description":"Lists and manages personal files within SingleStore workspaces through MCP tools, providing access to user-uploaded datasets, notebooks, and other workspace resources. The server queries the SingleStore Management API to enumerate available files and their metadata, enabling LLM clients to discover and reference resources for analysis.","intents":["I want Claude to list files I've uploaded to my workspace","I need the LLM to discover available datasets for analysis","I want to reference personal files in notebook creation without manual lookup"],"best_for":["Data analysts discovering personal datasets through LLM interfaces","Teams automating analysis workflows that reference uploaded files","LLM agents building data pipelines from workspace resources"],"limitations":["File listing is workspace-scoped — no cross-workspace file discovery","File metadata is limited to name, size, and timestamp — no content preview","No file upload capability through MCP tools — only listing and reference","File access control is workspace-level, not granular per-file"],"requires":["Python 3.11+","SingleStore Management API credentials with read permissions","Active workspace with uploaded files","MCP client with tool-calling capability"],"input_types":["workspace ID (string)","optional file type filter"],"output_types":["list of personal files with metadata","file names, sizes, and upload timestamps","file type and format information","file references for use in queries"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_8","uri":"capability://tool.use.integration.mcp.protocol.server.lifecycle.and.tool.registration","name":"mcp protocol server lifecycle and tool registration","description":"Implements the Model Context Protocol server specification, handling MCP client connections, tool registration, and request routing through a Python-based MCP server framework. The server registers all SingleStore tools with their schemas, handles protocol handshakes, and routes incoming tool calls to appropriate API handlers with error translation and response formatting.","intents":["I want to connect my LLM client to SingleStore through the standard MCP protocol","I need the MCP server to handle protocol negotiation and tool discovery automatically","I want to extend the MCP server with custom tools without modifying core protocol handling"],"best_for":["LLM client developers implementing MCP support","Teams standardizing on MCP for tool integration","Developers extending SingleStore MCP with custom tools"],"limitations":["MCP server is single-threaded — concurrent tool calls are queued sequentially","No built-in rate limiting — rapid tool calls may overwhelm SingleStore API","Tool schemas are static — no dynamic schema generation based on runtime state","Error handling is basic — API errors are translated to MCP error responses without detailed diagnostics"],"requires":["Python 3.11+","MCP-compatible LLM client (Claude Desktop, Cursor IDE, or compatible)","Network connectivity between MCP server and LLM client","Valid SingleStore credentials"],"input_types":["MCP protocol messages (tool calls, resource requests)","tool arguments matching registered schemas"],"output_types":["MCP protocol responses (tool results, errors)","structured tool output matching declared schemas"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-singlestore__cap_9","uri":"capability://automation.workflow.configuration.management.with.environment.based.credential.handling","name":"configuration management with environment-based credential handling","description":"Manages MCP server configuration through environment variables and configuration files, supporting multiple authentication methods (API keys, OAuth tokens) and deployment scenarios (local, Docker, Smithery). The server loads configuration at startup, validates required parameters, and provides fallback defaults for optional settings.","intents":["I want to configure the MCP server without editing code","I need to deploy the MCP server in Docker with environment-based configuration","I want to support multiple authentication methods in a single deployment"],"best_for":["DevOps engineers deploying MCP servers in containerized environments","Teams managing multiple MCP server instances with different configurations","Developers integrating MCP server into CI/CD pipelines"],"limitations":["Configuration is loaded at startup — changes require server restart","No built-in configuration validation — invalid settings may cause runtime failures","Environment variables are unencrypted — sensitive credentials should use external secret management","No configuration hot-reload — long-running servers cannot pick up configuration changes"],"requires":["Python 3.11+","Environment variables or configuration file with SingleStore credentials","Valid configuration format (YAML, JSON, or environment variables)"],"input_types":["environment variables (API_KEY, OAUTH_TOKEN, etc.)","configuration file (YAML or JSON format)","command-line arguments"],"output_types":["validated configuration object","configuration validation errors","default values for optional settings"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":27,"verified":false,"data_access_risk":"high","permissions":["Python 3.11+","Valid SingleStore Management API credentials (API key or OAuth token)","Active SingleStore workspace with network access from MCP server","MCP-compatible LLM client (Claude Desktop, Cursor IDE, or compatible)","SingleStore Management API credentials with workspace creation permissions","Active SingleStore organization with available workspace quota","MCP client with tool-calling capability","MCP server running with error handling enabled","SingleStore Management API credentials with notebook creation permissions","Active SingleStore workspace for notebook execution"],"failure_modes":["Query execution is synchronous — long-running queries may timeout depending on MCP client timeout settings","No built-in query result pagination — large result sets are returned in full, potentially exceeding context windows","Query results are formatted as plain text/JSON, not streamed, so memory usage scales with result size","No query optimization hints or execution plan analysis provided to the LLM","Workspace creation is asynchronous but MCP tool returns immediately — LLM must poll for readiness status","No built-in cost controls — runaway workspace creation could incur unexpected charges","Workspace deletion is permanent and non-recoverable through this interface","Resource sizing is limited to SingleStore's predefined workspace tiers, no custom resource allocation","Error translation is basic — complex API errors may not map to meaningful messages","No error categorization — LLM clients cannot distinguish between transient and permanent failures","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.32,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"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":"2026-06-17T09:51:04.049Z","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=singlestore","compare_url":"https://unfragile.ai/compare?artifact=singlestore"}},"signature":"naldqF8GX4x6RCmIps8UbRRLlSHU2+UFw2dKxvcaO0xc43i412vPgeiJceqtSSxYDXVQz+umiFoRu4hCP+T+CA==","signedAt":"2026-06-21T14:12:14.402Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/singlestore","artifact":"https://unfragile.ai/singlestore","verify":"https://unfragile.ai/api/v1/verify?slug=singlestore","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"}}