{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-targetprocess-mcp-server","slug":"npm-targetprocess-mcp-server","name":"targetprocess-mcp-server","type":"mcp","url":"https://www.npmjs.com/package/targetprocess-mcp-server","page_url":"https://unfragile.ai/npm-targetprocess-mcp-server","categories":["mcp-servers"],"tags":["mcp","tp","mcp-server","targetprocess","targetprocess-server"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-targetprocess-mcp-server__cap_0","uri":"capability://tool.use.integration.targetprocess.resource.crud.operations","name":"targetprocess-resource-crud-operations","description":"Exposes CRUD operations for Targetprocess entities (epics, features, bugs, tasks, user stories) through MCP tool bindings that map directly to Targetprocess REST API endpoints. Implements a schema-based function registry where each entity type has corresponding create, read, update, delete tools with typed parameters validated against Targetprocess data models. The MCP server translates tool calls into authenticated HTTP requests to Targetprocess cloud or on-premise instances.","intents":["I want to programmatically create and update work items in Targetprocess from an AI agent without manual API integration","I need to query Targetprocess entities by ID or filter criteria and retrieve structured data for downstream processing","I want to delete or archive Targetprocess items through an AI workflow without leaving the MCP context"],"best_for":["Teams using Targetprocess as their primary project management system and building AI agents that need to mutate work items","DevOps engineers automating Targetprocess workflows via Claude or other MCP-compatible LLMs","Organizations integrating Targetprocess with multi-tool AI orchestration platforms"],"limitations":["Requires valid Targetprocess API credentials (token or OAuth) — no anonymous access","Rate limiting enforced by Targetprocess API (typically 100-300 requests/minute depending on plan) may throttle high-volume agent operations","No built-in caching or batching — each tool call triggers a separate HTTP request, adding ~200-500ms latency per operation","Limited to Targetprocess API v1 or v2 capabilities — custom fields or enterprise-only features may not be exposed"],"requires":["Node.js 16+ (MCP server runtime)","Targetprocess API token or OAuth credentials with appropriate scopes","Network access to Targetprocess cloud (api.targetprocess.com) or on-premise instance URL","MCP-compatible client (Claude Desktop, custom MCP host, or compatible LLM platform)"],"input_types":["JSON-structured tool parameters (entity type, ID, field values)","Filter/query strings (e.g., 'state = \"Open\" AND priority = \"High\"')"],"output_types":["JSON-serialized Targetprocess entity objects","Structured arrays of matching entities with full metadata","Boolean success/failure responses for mutations"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-targetprocess-mcp-server__cap_1","uri":"capability://search.retrieval.targetprocess.entity.search.and.filtering","name":"targetprocess-entity-search-and-filtering","description":"Implements semantic and structured search across Targetprocess entities using the MCP server's query tool, which translates filter expressions into Targetprocess API query syntax (OData-style or native filters). Supports filtering by entity type, status, priority, assignee, custom fields, date ranges, and text search. Returns paginated result sets with configurable field projection to reduce payload size and improve performance.","intents":["I want to find all open bugs assigned to a specific team member across multiple projects","I need to retrieve high-priority epics created in the last 30 days for a status report","I want to search for work items by title or description text and get back matching entities with their metadata"],"best_for":["AI agents that need to discover and filter Targetprocess work items as part of decision-making workflows","Teams building custom dashboards or reporting tools that query Targetprocess data via LLM intermediaries","Developers creating multi-step workflows where LLMs must locate specific entities before performing mutations"],"limitations":["Search performance degrades with large result sets (>1000 items) — pagination required but adds round-trip latency","Text search may not support full-text indexing features available in Targetprocess UI — limited to exact field matching","Custom field filtering depends on Targetprocess schema exposure via API — some enterprise custom fields may not be queryable","No full-text search across all entity fields — must specify which fields to search explicitly"],"requires":["Node.js 16+","Targetprocess API token with read permissions on target projects/entities","Network access to Targetprocess instance","MCP-compatible client"],"input_types":["Filter expressions (e.g., 'state = \"Open\" AND priority = \"High\"')","Entity type identifiers (epic, feature, bug, task, user story)","Field names and comparison operators (=, !=, <, >, contains, etc.)"],"output_types":["Paginated JSON arrays of matching entities","Entity metadata with configurable field projection","Total count and pagination tokens for result set navigation"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-targetprocess-mcp-server__cap_2","uri":"capability://memory.knowledge.targetprocess.project.and.portfolio.context.retrieval","name":"targetprocess-project-and-portfolio-context-retrieval","description":"Provides MCP tools to retrieve hierarchical project structure, portfolio metadata, and team/resource information from Targetprocess. Fetches project lists, project details (including custom fields, workflows, team members), and portfolio-level aggregations. Caches project metadata to reduce API calls for frequently accessed context, implementing a simple in-memory cache with configurable TTL to balance freshness and performance.","intents":["I want to understand the project structure and available teams before creating a new work item","I need to retrieve all projects in a portfolio to generate a cross-project status report","I want to get team member lists and their current workload to assign tasks intelligently"],"best_for":["AI agents that need to understand Targetprocess organizational context before making decisions or mutations","Multi-project workflows where LLMs must navigate project hierarchies and team structures","Reporting and analytics tools that aggregate data across multiple Targetprocess projects"],"limitations":["In-memory caching is not persistent — cache is lost on server restart, requiring re-fetch of project metadata","No built-in cache invalidation strategy — stale project data may be served if Targetprocess structure changes during server uptime","Large portfolios (>100 projects) may incur significant API overhead on initial context load","Team member workload calculations are point-in-time snapshots — do not reflect real-time capacity changes"],"requires":["Node.js 16+","Targetprocess API token with read permissions on projects and portfolio","Network access to Targetprocess instance","MCP-compatible client"],"input_types":["Project ID or portfolio ID","Optional filter parameters (e.g., active projects only)"],"output_types":["Hierarchical project structure with metadata","Team member lists with role and assignment information","Portfolio-level aggregations (total items, status distribution, etc.)"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-targetprocess-mcp-server__cap_3","uri":"capability://safety.moderation.targetprocess.workflow.state.transition.enforcement","name":"targetprocess-workflow-state-transition-enforcement","description":"Enforces valid state transitions for Targetprocess entities by validating workflow rules before allowing mutations. Retrieves workflow definitions from Targetprocess (valid state transitions, required fields for each state) and applies them as constraints on update operations. Prevents invalid state changes (e.g., moving a task directly from 'Open' to 'Closed' if workflow requires intermediate 'In Progress' state) and returns detailed error messages explaining why a transition is invalid.","intents":["I want to ensure that AI agents only perform valid state transitions that respect Targetprocess workflow rules","I need to get a list of valid next states for a work item before attempting to update it","I want to prevent invalid workflow transitions that would violate business process rules"],"best_for":["Teams with strict workflow governance that need AI agents to respect process rules","Organizations where invalid state transitions create data integrity issues or audit compliance problems","Workflows where LLMs must understand valid next states before proposing state changes to users"],"limitations":["Workflow validation adds ~100-300ms latency per state transition (requires fetching workflow definition if not cached)","Complex workflows with conditional transitions (e.g., 'can transition to Closed only if all subtasks are done') may not be fully enforced by the MCP server — requires custom validation logic","No support for workflow-level permissions or role-based state restrictions — only validates structural transitions","Workflow definitions are cached — changes to workflows in Targetprocess may not be reflected immediately in the MCP server"],"requires":["Node.js 16+","Targetprocess API token with read permissions on workflow definitions","Network access to Targetprocess instance","MCP-compatible client"],"input_types":["Entity type and ID","Proposed new state value","Current entity state (for validation context)"],"output_types":["Boolean validation result (valid/invalid transition)","List of valid next states for an entity","Detailed error message explaining why a transition is invalid"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-targetprocess-mcp-server__cap_4","uri":"capability://data.processing.analysis.targetprocess.custom.field.mapping.and.serialization","name":"targetprocess-custom-field-mapping-and-serialization","description":"Handles serialization and deserialization of Targetprocess custom fields (user-defined fields with custom data types) into JSON-compatible formats for MCP tool parameters. Maps custom field types (dropdowns, multi-select, date pickers, rich text, etc.) to appropriate JSON representations and validates input values against field constraints (allowed values, format requirements). Automatically converts between Targetprocess internal field IDs and human-readable field names for improved LLM usability.","intents":["I want to create or update work items with custom fields without needing to know internal Targetprocess field IDs","I need to handle custom field types (dropdowns, multi-select, dates) correctly when creating work items via AI agents","I want to serialize custom field values from Targetprocess into readable formats for LLM processing"],"best_for":["Organizations with extensive custom field usage in Targetprocess that need AI agents to populate them correctly","Teams where custom fields encode critical business data (e.g., customer tier, SLA level) that LLMs must understand and set","Workflows that require mapping between human-readable field names and Targetprocess internal field IDs"],"limitations":["Custom field schema must be fetched from Targetprocess API — adds initial setup latency and requires caching for performance","Complex custom field types (rich text, nested objects) may not serialize cleanly to JSON — may require custom serialization logic per field type","Validation of custom field constraints (e.g., allowed values for dropdowns) depends on Targetprocess schema exposure — some constraints may not be queryable","No support for custom field dependencies or conditional visibility rules — only validates individual field constraints"],"requires":["Node.js 16+","Targetprocess API token with read permissions on custom field definitions","Network access to Targetprocess instance","MCP-compatible client"],"input_types":["Custom field names (human-readable or internal IDs)","Field values in various formats (strings, arrays, dates, objects)","Field type information from Targetprocess schema"],"output_types":["JSON-serialized custom field values","Validated field values with constraint checking","Mapping between human-readable names and internal field IDs"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-targetprocess-mcp-server__cap_5","uri":"capability://automation.workflow.targetprocess.batch.operations.with.error.recovery","name":"targetprocess-batch-operations-with-error-recovery","description":"Provides MCP tools for batch operations (create, update, or delete multiple work items in a single tool call) with partial failure handling and error recovery. Implements transactional semantics where possible (e.g., all-or-nothing for related items) and graceful degradation for partial failures (e.g., 8 of 10 items created successfully). Returns detailed error reports per item, allowing LLMs to understand which operations succeeded and which failed, and optionally retry failed items.","intents":["I want to create multiple related work items (e.g., epic with child features) in a single operation without manual sequencing","I need to bulk-update work items with error recovery — if some updates fail, I want to know which ones and why","I want to perform batch operations efficiently without triggering rate limits from repeated single-item API calls"],"best_for":["AI workflows that need to create or update multiple related work items atomically","Teams bulk-importing data into Targetprocess via LLM agents with error visibility","High-volume automation scenarios where batch operations reduce API overhead and improve throughput"],"limitations":["Targetprocess API may not support true transactions — batch operations may be partially applied if some items fail, requiring manual rollback","Error recovery is best-effort — no automatic retry logic; LLMs must explicitly request retries for failed items","Batch size limits depend on Targetprocess API (typically 100-500 items per request) — very large batches may need to be split","No built-in deduplication — if batch contains duplicate items, both may be created, requiring manual cleanup"],"requires":["Node.js 16+","Targetprocess API token with write permissions","Network access to Targetprocess instance","MCP-compatible client"],"input_types":["Array of entity objects (create/update payloads)","Optional batch configuration (transaction mode, error handling strategy)"],"output_types":["Batch result object with success/failure counts","Detailed error report per failed item (error code, message, field-level validation errors)","Array of created/updated entity IDs for successful operations"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-targetprocess-mcp-server__cap_6","uri":"capability://search.retrieval.targetprocess.audit.and.change.tracking","name":"targetprocess-audit-and-change-tracking","description":"Exposes Targetprocess audit logs and change history through MCP tools, allowing LLMs to retrieve who changed what and when for any work item. Fetches change history with field-level granularity (old value, new value, timestamp, user who made the change) and supports filtering by date range, user, or change type. Enables audit-trail queries for compliance, debugging, or understanding the evolution of work items over time.","intents":["I want to retrieve the change history of a work item to understand how it evolved and who made each change","I need to find all changes made by a specific user in a date range for audit or compliance purposes","I want to understand what changed between two points in time for a work item or set of items"],"best_for":["Teams with compliance or audit requirements that need to track work item changes","Debugging workflows where understanding the history of a work item is critical","Reporting tools that need to analyze change patterns or user activity over time"],"limitations":["Audit log retrieval may be slow for items with extensive change history (>1000 changes) — pagination required","Targetprocess audit logs may have retention limits (e.g., 90 days) — historical data beyond retention period is unavailable","Field-level change tracking depends on Targetprocess audit configuration — some fields may not be tracked","No real-time change notifications — audit logs are historical only, not suitable for live change detection"],"requires":["Node.js 16+","Targetprocess API token with read permissions on audit logs","Network access to Targetprocess instance","MCP-compatible client"],"input_types":["Entity type and ID","Optional filters (date range, user, change type)"],"output_types":["Paginated array of change records with field-level details","Change metadata (timestamp, user, change type, old/new values)","Summary statistics (total changes, change frequency, etc.)"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":29,"verified":false,"data_access_risk":"high","permissions":["Node.js 16+ (MCP server runtime)","Targetprocess API token or OAuth credentials with appropriate scopes","Network access to Targetprocess cloud (api.targetprocess.com) or on-premise instance URL","MCP-compatible client (Claude Desktop, custom MCP host, or compatible LLM platform)","Node.js 16+","Targetprocess API token with read permissions on target projects/entities","Network access to Targetprocess instance","MCP-compatible client","Targetprocess API token with read permissions on projects and portfolio","Targetprocess API token with read permissions on workflow definitions"],"failure_modes":["Requires valid Targetprocess API credentials (token or OAuth) — no anonymous access","Rate limiting enforced by Targetprocess API (typically 100-300 requests/minute depending on plan) may throttle high-volume agent operations","No built-in caching or batching — each tool call triggers a separate HTTP request, adding ~200-500ms latency per operation","Limited to Targetprocess API v1 or v2 capabilities — custom fields or enterprise-only features may not be exposed","Search performance degrades with large result sets (>1000 items) — pagination required but adds round-trip latency","Text search may not support full-text indexing features available in Targetprocess UI — limited to exact field matching","Custom field filtering depends on Targetprocess schema exposure via API — some enterprise custom fields may not be queryable","No full-text search across all entity fields — must specify which fields to search explicitly","In-memory caching is not persistent — cache is lost on server restart, requiring re-fetch of project metadata","No built-in cache invalidation strategy — stale project data may be served if Targetprocess structure changes during server uptime","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.24,"ecosystem":0.45,"match_graph":0.25,"freshness":0.75,"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":"2026-05-24T12:16:24.483Z","last_scraped_at":"2026-04-22T08:09:32.964Z","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=npm-targetprocess-mcp-server","compare_url":"https://unfragile.ai/compare?artifact=npm-targetprocess-mcp-server"}},"signature":"/Lr+Jo5PDo6ufn5pJSZxoM5etr4p7rfoUzuqihaA/4YT0GQsXqN5Dfn2fSslAg/hYHIk3kZci8lxC9FMcGooDw==","signedAt":"2026-06-22T14:55:59.376Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-targetprocess-mcp-server","artifact":"https://unfragile.ai/npm-targetprocess-mcp-server","verify":"https://unfragile.ai/api/v1/verify?slug=npm-targetprocess-mcp-server","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"}}