{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"smithery_0x3at-tasks","slug":"0x3at-tasks","name":"tasks","type":"mcp","url":"https://smithery.ai/servers/0x3at/tasks","page_url":"https://unfragile.ai/0x3at-tasks","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","smithery:0x3at/tasks"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"smithery_0x3at-tasks__cap_0","uri":"capability://tool.use.integration.task.creation.via.mcp.protocol","name":"task-creation-via-mcp-protocol","description":"Creates new tasks through the Model Context Protocol by exposing a standardized tool interface that LLM clients can invoke. The server implements MCP's tool definition schema, allowing Claude, other LLM agents, or MCP-compatible clients to define task properties (title, description, priority, due date) and persist them to a backend store. Works by registering task creation as a callable tool with JSON schema validation, enabling type-safe task instantiation from natural language or structured prompts.","intents":["I want my AI agent to create tasks programmatically without custom API integration","I need tasks created from Claude conversations to persist in my task management system","I want to expose task creation as a standardized capability that any MCP client can use"],"best_for":["AI agent developers building autonomous task management workflows","Teams integrating Claude or other LLMs with existing task systems via MCP","Builders prototyping AI-driven productivity tools with standardized protocols"],"limitations":["Requires MCP-compatible client (Claude, custom agents) — no REST API fallback","Task schema is fixed by server implementation — no dynamic field customization","No built-in conflict resolution if multiple agents create tasks simultaneously"],"requires":["MCP client implementation (Claude, Anthropic SDK, or custom MCP host)","Network connectivity to MCP server endpoint","Understanding of MCP tool schema format and invocation patterns"],"input_types":["JSON-structured tool arguments (title, description, priority, dueDate, etc.)","Natural language from LLM that gets converted to tool arguments"],"output_types":["JSON task object with ID, creation timestamp, and status","MCP tool result with success/error status"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_0x3at-tasks__cap_1","uri":"capability://tool.use.integration.task.listing.with.mcp.resource.protocol","name":"task-listing-with-mcp-resource-protocol","description":"Exposes tasks as MCP resources that clients can read and subscribe to, implementing the MCP resource protocol for standardized task retrieval. The server maintains a resource URI scheme (e.g., 'task://all' or 'task://filter?status=open') and returns task lists as structured JSON. Clients can request resources directly or subscribe to updates, enabling real-time task synchronization without polling. Uses MCP's resource subscription mechanism to push changes to connected clients.","intents":["I want my AI agent to read the current task list before deciding on actions","I need real-time task updates pushed to my MCP client without polling","I want to filter tasks by status, priority, or other criteria through a standard protocol"],"best_for":["AI agents that need task context before making decisions","Dashboard or UI applications consuming tasks via MCP","Multi-agent systems requiring synchronized task state"],"limitations":["Resource filtering depends on server-side implementation — no client-side query language","Subscription updates are server-initiated — no client-side filtering of pushed updates","Large task lists may exceed MCP message size limits without pagination"],"requires":["MCP client with resource protocol support","Server-side task storage (database or file system)","Network connection to MCP server for subscription updates"],"input_types":["MCP resource URI with optional query parameters","Subscription requests with resource path"],"output_types":["JSON array of task objects","Streamed resource updates for subscriptions","Metadata (total count, pagination info)"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_0x3at-tasks__cap_2","uri":"capability://tool.use.integration.task.update.with.atomic.mutations","name":"task-update-with-atomic-mutations","description":"Modifies existing tasks through MCP tool calls that apply atomic mutations (status changes, priority updates, due date modifications, description edits). The server implements optimistic locking or version-based conflict detection to prevent race conditions when multiple agents or clients update the same task. Updates are validated against the task schema before persistence, ensuring data integrity. Returns the updated task object with new timestamps and version identifiers.","intents":["I want my AI agent to mark tasks complete or update their status based on work completion","I need to change task priority or due dates programmatically without manual intervention","I want safe concurrent updates where conflicts are detected and resolved"],"best_for":["Autonomous agents that complete tasks and need to update state","Multi-agent systems where concurrent task modifications must be safe","Workflow automation that progresses tasks through state machines"],"limitations":["No partial updates — entire task object may need to be re-sent depending on implementation","Conflict resolution strategy (last-write-wins vs. merge) is server-determined","No audit trail or change history unless explicitly implemented"],"requires":["MCP client with tool invocation support","Task ID or unique identifier for the task being updated","Appropriate permissions/authentication (if implemented)"],"input_types":["JSON object with task ID and fields to update (status, priority, dueDate, description, etc.)","Optional version/etag for optimistic locking"],"output_types":["Updated task JSON object with new timestamps","Version/etag for subsequent updates","Conflict error if concurrent modification detected"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_0x3at-tasks__cap_3","uri":"capability://tool.use.integration.task.deletion.with.soft.delete.semantics","name":"task-deletion-with-soft-delete-semantics","description":"Removes tasks from active view through MCP tool calls that implement soft-delete semantics (marking tasks as deleted rather than purging records). The server maintains a deletion timestamp and optional reason, preserving audit trails and enabling recovery. Hard deletion may be available through separate administrative tools. Deleted tasks are excluded from default list queries but can be retrieved through explicit archived/deleted task resources.","intents":["I want my agent to remove completed or obsolete tasks from the active list","I need to preserve task history for auditing while hiding deleted tasks from normal views","I want the ability to recover accidentally deleted tasks"],"best_for":["Production task systems requiring audit trails","Agents that clean up completed or cancelled tasks","Organizations with compliance requirements for data retention"],"limitations":["Soft deletes increase storage overhead — deleted records remain in database","Queries must explicitly filter out deleted tasks — no automatic exclusion","Hard deletion (if available) is typically restricted to administrators"],"requires":["MCP client with tool invocation","Task ID of the task to delete","Optional deletion reason or metadata"],"input_types":["JSON with task ID and optional deletion reason","Boolean flag to distinguish soft vs. hard delete (if supported)"],"output_types":["Confirmation JSON with deletion timestamp","Updated task object with deleted flag","Error if task already deleted or not found"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_0x3at-tasks__cap_4","uri":"capability://search.retrieval.task.filtering.and.querying.via.mcp.resources","name":"task-filtering-and-querying-via-mcp-resources","description":"Provides filtered task views through MCP resource URIs with query parameters (status, priority, assignee, due date range, tags). The server parses resource requests and returns filtered task subsets without requiring separate tool calls. Supports common filtering patterns like 'tasks://open', 'tasks://high-priority', 'tasks://due-today'. Filtering is performed server-side, reducing client-side processing and enabling efficient pagination of large task sets.","intents":["I want my agent to query only high-priority or overdue tasks before deciding on actions","I need to retrieve tasks assigned to a specific person or team","I want to filter tasks by multiple criteria (status AND priority AND due date)"],"best_for":["Agents that need contextual task subsets for decision-making","Dashboard applications displaying filtered task views","Workflow systems that route tasks based on status or priority"],"limitations":["Filter operators are predefined by server — no arbitrary query language","Complex multi-criteria filters may require multiple resource requests","No full-text search unless explicitly implemented"],"requires":["MCP client with resource protocol support","Knowledge of available filter parameters and syntax","Server-side indexing for efficient filtering (optional but recommended)"],"input_types":["MCP resource URI with query parameters (e.g., 'tasks://filter?status=open&priority=high')","Pagination parameters (limit, offset)"],"output_types":["Filtered JSON array of task objects","Metadata with total matching count","Pagination cursors for large result sets"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_0x3at-tasks__cap_5","uri":"capability://tool.use.integration.task.schema.introspection.via.mcp","name":"task-schema-introspection-via-mcp","description":"Exposes the task data model schema through MCP's capability discovery mechanism, allowing clients to understand task properties, required fields, valid enums (for status, priority), and constraints without hardcoding. The server provides a schema resource or tool that returns JSON Schema definitions for task objects. Clients use this to validate inputs before calling task creation/update tools, and to render dynamic UIs based on the schema.","intents":["I want my agent to understand what fields are required when creating a task","I need to validate task data before sending it to the server","I want to build a dynamic UI that adapts to the task schema without hardcoding field names"],"best_for":["Generic MCP clients that work with multiple task servers","Agents that need to validate inputs before tool invocation","UI frameworks building dynamic forms from server schemas"],"limitations":["Schema changes require server updates — no client-side schema versioning","Complex validation rules may not be expressible in JSON Schema","Schema introspection adds latency to client initialization"],"requires":["MCP client with schema introspection support","Server implementation of schema resource or tool"],"input_types":["MCP introspection request (no input required)","Optional schema version parameter"],"output_types":["JSON Schema object defining task properties","Enum definitions for status, priority, etc.","Validation constraints (min/max, regex patterns)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_0x3at-tasks__cap_6","uri":"capability://planning.reasoning.task.agent.integration.with.planning.context","name":"task-agent-integration-with-planning-context","description":"Integrates task management into LLM agent planning loops by exposing tasks as contextual resources that agents read before deciding on actions. The server provides task state snapshots that agents use in chain-of-thought reasoning (e.g., 'I see 3 high-priority tasks, I should focus on the one due today'). Agents can invoke task mutations as part of multi-step plans, with the server tracking task state changes across plan execution. Enables agents to reason about task dependencies and sequencing.","intents":["I want my agent to consider current tasks when planning its next actions","I need my agent to update task state as part of a multi-step workflow","I want my agent to reason about task priorities and dependencies before acting"],"best_for":["Autonomous agents executing multi-step workflows","AI assistants that manage user task lists","Agents that need task context for decision-making"],"limitations":["Agent planning is non-deterministic — same task state may lead to different actions","No built-in task dependency tracking — agents must infer dependencies from descriptions","Large task lists may exceed context windows, requiring filtering"],"requires":["LLM agent framework with MCP support (e.g., Claude with MCP tools)","Task server exposing tasks as resources or tools","Agent prompting that instructs consideration of task state"],"input_types":["Task list as context in agent prompt","Task state updates from agent tool invocations"],"output_types":["Agent reasoning trace showing task consideration","Task mutations executed as part of plan","Updated task state after plan execution"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":25,"verified":false,"data_access_risk":"high","permissions":["MCP client implementation (Claude, Anthropic SDK, or custom MCP host)","Network connectivity to MCP server endpoint","Understanding of MCP tool schema format and invocation patterns","MCP client with resource protocol support","Server-side task storage (database or file system)","Network connection to MCP server for subscription updates","MCP client with tool invocation support","Task ID or unique identifier for the task being updated","Appropriate permissions/authentication (if implemented)","MCP client with tool invocation"],"failure_modes":["Requires MCP-compatible client (Claude, custom agents) — no REST API fallback","Task schema is fixed by server implementation — no dynamic field customization","No built-in conflict resolution if multiple agents create tasks simultaneously","Resource filtering depends on server-side implementation — no client-side query language","Subscription updates are server-initiated — no client-side filtering of pushed updates","Large task lists may exceed MCP message size limits without pagination","No partial updates — entire task object may need to be re-sent depending on implementation","Conflict resolution strategy (last-write-wins vs. merge) is server-determined","No audit trail or change history unless explicitly implemented","Soft deletes increase storage overhead — deleted records remain in database","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.24,"ecosystem":0.38999999999999996,"match_graph":0.25,"freshness":0.5,"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":"2026-05-24T12:16:25.061Z","last_scraped_at":"2026-05-03T15:19:44.684Z","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=0x3at-tasks","compare_url":"https://unfragile.ai/compare?artifact=0x3at-tasks"}},"signature":"s5ZxFCR2nOsaKOdtiFXROvss1uOOwFQw/DGAD3e/TvSKNYjYCV2ApQY3UlDZB2YHyF8Fafbv03Xjqezkrv6zBQ==","signedAt":"2026-06-21T09:16:01.153Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/0x3at-tasks","artifact":"https://unfragile.ai/0x3at-tasks","verify":"https://unfragile.ai/api/v1/verify?slug=0x3at-tasks","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"}}