{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-jira-context-mcp","slug":"jira-context-mcp","name":"Jira Context MCP","type":"mcp","url":"https://github.com/rahulthedevil/Jira-Context-MCP","page_url":"https://unfragile.ai/jira-context-mcp","categories":["mcp-servers","app-builders"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-jira-context-mcp__cap_0","uri":"capability://tool.use.integration.jira.ticket.context.injection.into.ai.coding.agents","name":"jira ticket context injection into ai coding agents","description":"Implements an MCP (Model Context Protocol) server that exposes Jira ticket data as tools callable by AI coding agents like Cursor. The server acts as a bridge between Jira's REST API and MCP-compatible clients, translating ticket metadata (issue keys, summaries, descriptions, status, assignees) into structured tool schemas that agents can invoke during code generation workflows. This enables agents to fetch real-time ticket context without requiring direct API credentials or manual context copying.","intents":["I want my AI coding agent to automatically fetch the Jira ticket I'm working on without me manually copying the description","I need the AI agent to understand the current ticket status and requirements while generating code","I want to avoid context switching between Jira and my IDE when the agent needs ticket details"],"best_for":["Development teams using Cursor or other MCP-compatible AI coding agents","Teams with Jira-centric workflows who want seamless agent integration","Solo developers building LLM-powered coding assistants with Jira backends"],"limitations":["Requires Jira API credentials (username/API token) to be configured in the MCP server environment","No built-in caching — each agent request triggers a fresh API call to Jira, adding latency","Limited to read-only Jira operations; cannot create, update, or transition tickets through the MCP interface","Depends on MCP client support — only works with tools that implement the MCP specification (Cursor, Claude Desktop, etc.)"],"requires":["Jira Cloud or Server instance with REST API access","Jira API token or username/password credentials","MCP-compatible AI coding agent (Cursor, Claude Desktop, or custom MCP client)","Python 3.8+ (if running the server locally)","Network access to Jira instance from the MCP server"],"input_types":["Jira issue key (string, e.g., 'PROJ-123')","JQL query strings (optional, for ticket search)","MCP tool invocation payloads (JSON)"],"output_types":["structured JSON with ticket metadata (key, summary, description, status, assignee, priority, labels)","MCP tool result objects (JSON)","error messages with Jira API error details"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-jira-context-mcp__cap_1","uri":"capability://memory.knowledge.real.time.jira.ticket.metadata.retrieval.via.mcp.tools","name":"real-time jira ticket metadata retrieval via mcp tools","description":"Exposes Jira ticket data through MCP tool definitions that agents can call with ticket identifiers. The server queries Jira's REST API endpoints (typically /rest/api/3/issue/{key}) and returns structured metadata including issue key, summary, description, current status, assignee, priority, labels, and custom fields. The MCP protocol wraps these calls in a standardized tool schema, allowing agents to discover and invoke ticket lookups as part of their reasoning chain.","intents":["I want the agent to look up the current status of a ticket before suggesting code changes","I need the agent to read the full ticket description to understand acceptance criteria","I want the agent to know who is assigned to a ticket and what priority it has"],"best_for":["Teams where AI agents need to make context-aware coding decisions based on live ticket data","Workflows where ticket status or priority should influence code generation strategy","Developers who want agents to validate requirements against Jira before implementing"],"limitations":["Retrieval latency depends on Jira instance performance and network conditions (typically 200-800ms per request)","No support for custom field mappings — returns only standard Jira fields unless explicitly configured","Cannot retrieve ticket history or comments; only current state is available","Rate-limited by Jira API quotas (typically 180 requests per minute for cloud instances)"],"requires":["Valid Jira issue key format (e.g., 'PROJ-123')","Jira API authentication credentials configured in MCP server","Network connectivity to Jira instance","MCP client that supports tool invocation (Cursor, Claude Desktop)"],"input_types":["Jira issue key (string)","optional: custom field names to include in response"],"output_types":["JSON object with ticket metadata","null or error if ticket not found","MCP error response with HTTP status code"],"categories":["memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-jira-context-mcp__cap_2","uri":"capability://tool.use.integration.mcp.protocol.server.implementation.for.jira.integration","name":"mcp protocol server implementation for jira integration","description":"Implements a full MCP (Model Context Protocol) server that handles MCP client connections, tool schema registration, and request/response marshaling. The server exposes Jira operations as MCP tools with defined input schemas and output formats, handles authentication between the MCP client and Jira backend, and manages the lifecycle of connections from MCP-compatible clients like Cursor. This enables any MCP-aware application to treat Jira as a callable service without implementing Jira-specific logic.","intents":["I want to use Jira data in any MCP-compatible AI tool without rebuilding the integration","I need a standardized way to expose Jira to multiple AI agents and applications","I want to avoid vendor lock-in by using the open MCP protocol instead of proprietary APIs"],"best_for":["Teams building multiple MCP-compatible AI tools who want a single Jira integration point","Organizations standardizing on MCP for AI agent integrations","Developers creating custom MCP clients that need Jira access"],"limitations":["MCP protocol overhead adds ~50-100ms per request compared to direct REST API calls","Requires MCP client support — cannot be used with non-MCP tools or older AI platforms","No built-in load balancing or clustering — single server instance may become a bottleneck","Limited error recovery — MCP protocol does not define retry semantics, relying on client-side retry logic"],"requires":["MCP server implementation library (e.g., mcp Python package or Node.js equivalent)","Jira REST API credentials","MCP-compatible client (Cursor, Claude Desktop, or custom implementation)","Python 3.8+ or Node.js 16+ depending on server implementation"],"input_types":["MCP initialization messages (JSON-RPC 2.0)","MCP tool call requests with parameters","MCP resource requests (if resources are exposed)"],"output_types":["MCP tool result responses (JSON)","MCP error responses with error codes","MCP resource data (if applicable)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-jira-context-mcp__cap_3","uri":"capability://safety.moderation.jira.api.credential.management.and.authentication","name":"jira api credential management and authentication","description":"Manages Jira API authentication credentials (API tokens, username/password, or OAuth) and applies them to all outbound Jira REST API requests. The server stores credentials securely (typically via environment variables or configuration files) and injects them into HTTP headers (Authorization: Basic or Bearer tokens) for each API call. This decouples credential management from MCP clients, preventing credential exposure and centralizing authentication logic.","intents":["I want to configure Jira access once on the MCP server without sharing credentials with each AI agent","I need to rotate Jira API tokens without updating every client configuration","I want to ensure Jira credentials are never exposed to the AI agent or its context"],"best_for":["Teams with security-conscious credential management policies","Environments where multiple AI agents share a single Jira backend","Organizations requiring credential rotation and audit trails"],"limitations":["Credentials stored in environment variables or config files are vulnerable to local privilege escalation attacks","No built-in credential rotation — requires manual updates or external secret management integration","No audit logging of credential usage — cannot track which agents accessed Jira or when","Supports only Jira Cloud/Server authentication; does not support advanced OAuth flows or SAML"],"requires":["Jira API token (recommended) or username/password pair","Environment variable or configuration file to store credentials","Secure file permissions on configuration files (chmod 600 or equivalent)"],"input_types":["Jira API token (string)","Jira username (string)","Jira password or API token (string)"],"output_types":["HTTP Authorization headers (injected into requests)","authentication success/failure status"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-jira-context-mcp__cap_4","uri":"capability://search.retrieval.jira.ticket.search.and.filtering.via.jql.queries","name":"jira ticket search and filtering via jql queries","description":"Exposes Jira Query Language (JQL) search capabilities through MCP tools, allowing agents to search for tickets matching specific criteria (assignee, status, priority, labels, custom fields). The server translates JQL queries into Jira REST API search endpoints (/rest/api/3/search) and returns paginated results with ticket metadata. This enables agents to discover relevant tickets without requiring explicit ticket keys, supporting dynamic ticket lookup based on context.","intents":["I want the agent to find all open tickets assigned to me without me specifying each ticket key","I need the agent to search for tickets with a specific label or priority to understand related work","I want the agent to discover tickets matching a search query based on description or summary"],"best_for":["Workflows where agents need to discover tickets dynamically rather than using pre-specified keys","Teams with large backlogs where agents should filter by status, assignee, or priority","Scenarios where agents need to understand related or dependent work"],"limitations":["JQL query complexity can impact Jira performance; complex queries may timeout or return partial results","Pagination requires multiple API calls for large result sets, increasing latency","No support for full-text search across ticket descriptions — limited to indexed fields","JQL syntax is Jira-specific; agents must be trained to generate valid JQL or rely on predefined query templates"],"requires":["Valid JQL query syntax","Jira API credentials with search permissions","Understanding of Jira field names and custom field IDs for advanced queries"],"input_types":["JQL query string (e.g., 'assignee = currentUser() AND status = Open')","optional: pagination parameters (maxResults, startAt)"],"output_types":["JSON array of ticket objects with metadata","pagination metadata (total count, startAt, maxResults)","error message if JQL is invalid"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-jira-context-mcp__cap_5","uri":"capability://tool.use.integration.mcp.tool.schema.definition.and.discovery","name":"mcp tool schema definition and discovery","description":"Defines and exposes MCP tool schemas that describe available Jira operations (get ticket, search tickets, etc.) with input parameter definitions, output formats, and descriptions. MCP clients use these schemas to discover available tools, validate input parameters, and understand expected outputs. The server implements the MCP tools/list and tools/call endpoints to support tool discovery and invocation, enabling clients to dynamically discover Jira capabilities without hardcoding tool names or parameters.","intents":["I want the AI agent to discover what Jira operations are available without me telling it","I need the agent to understand what parameters each Jira tool requires and what it returns","I want to add new Jira tools to the MCP server and have agents automatically discover them"],"best_for":["MCP clients that support dynamic tool discovery (Cursor, Claude Desktop)","Scenarios where tool availability may change and clients need to adapt","Teams building custom MCP clients that need to introspect available tools"],"limitations":["Schema definitions must be manually maintained — no automatic generation from Jira API specs","Tool discovery adds overhead to MCP initialization (typically 50-200ms)","Schema changes require server restart; no hot-reloading of tool definitions","Complex nested schemas may not be fully supported by all MCP clients"],"requires":["MCP server implementation with tools/list and tools/call support","JSON schema definitions for each tool's input and output"],"input_types":["MCP tools/list request (no parameters)","MCP tools/call request with tool name and parameters"],"output_types":["JSON array of tool definitions with schemas","MCP tool result or error response"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"high","permissions":["Jira Cloud or Server instance with REST API access","Jira API token or username/password credentials","MCP-compatible AI coding agent (Cursor, Claude Desktop, or custom MCP client)","Python 3.8+ (if running the server locally)","Network access to Jira instance from the MCP server","Valid Jira issue key format (e.g., 'PROJ-123')","Jira API authentication credentials configured in MCP server","Network connectivity to Jira instance","MCP client that supports tool invocation (Cursor, Claude Desktop)","MCP server implementation library (e.g., mcp Python package or Node.js equivalent)"],"failure_modes":["Requires Jira API credentials (username/API token) to be configured in the MCP server environment","No built-in caching — each agent request triggers a fresh API call to Jira, adding latency","Limited to read-only Jira operations; cannot create, update, or transition tickets through the MCP interface","Depends on MCP client support — only works with tools that implement the MCP specification (Cursor, Claude Desktop, etc.)","Retrieval latency depends on Jira instance performance and network conditions (typically 200-800ms per request)","No support for custom field mappings — returns only standard Jira fields unless explicitly configured","Cannot retrieve ticket history or comments; only current state is available","Rate-limited by Jira API quotas (typically 180 requests per minute for cloud instances)","MCP protocol overhead adds ~50-100ms per request compared to direct REST API calls","Requires MCP client support — cannot be used with non-MCP tools or older AI platforms","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.22,"ecosystem":0.49999999999999994,"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":"2026-06-17T09:51:03.577Z","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=jira-context-mcp","compare_url":"https://unfragile.ai/compare?artifact=jira-context-mcp"}},"signature":"1VzrPOfdmuCyhli0vnYwhryYnYEPRSNQi12Ey2zmeB6K3aXCb9ELw1xhnFyXzrJisRHrj5wgZj3bGpxEIgvJBA==","signedAt":"2026-06-22T10:49:38.958Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/jira-context-mcp","artifact":"https://unfragile.ai/jira-context-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=jira-context-mcp","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"}}