Jira MCP Server
MCP ServerFree** A modular and extensible MCP server designed to interact with Jira Cloud, providing tools to query boards, issues, and user data — ideal for integrating Jira with AI agents, bots, or automation systems
Capabilities11 decomposed
jira board state querying with mcp protocol binding
Medium confidenceExposes Jira Cloud board data (sprints, columns, swimlanes, board settings) through MCP tool endpoints that serialize board state into structured JSON. Uses Jira REST API v3 under the hood with MCP's request-response pattern to translate tool calls into authenticated API requests, returning board metadata and configuration without polling overhead.
Implements MCP tool protocol as a native binding layer to Jira REST API v3, allowing LLM agents to query board state without custom HTTP client code; modular design separates board queries from issue/user operations for independent scaling
Lighter than full Jira SDK integrations (no heavy client library) and more structured than raw REST API calls, with MCP protocol ensuring compatibility with any MCP-aware LLM host (Claude, custom agents)
issue search and filtering with jql translation
Medium confidenceTranslates natural language or structured filter parameters into Jira Query Language (JQL) and executes searches against Jira Cloud, returning paginated issue results with full issue details (fields, history, transitions). Uses MCP tool endpoints to expose search as a callable function, handling JQL syntax generation and result pagination internally.
Exposes Jira's native JQL search engine as an MCP tool, allowing agents to leverage Jira's full query syntax without reimplementing search logic; handles pagination and result marshaling transparently
More powerful than simple field-based filters because it uses JQL (Jira's native query language), enabling complex boolean logic and custom field searches; simpler than building a custom search DSL
webhook event subscription and event streaming (if supported)
Medium confidenceunknown — insufficient data. The repository description does not specify whether the MCP server supports webhook subscriptions or event streaming. If implemented, this would likely use Jira Cloud webhooks to stream issue events (created, updated, transitioned) to MCP clients via server-sent events or similar streaming mechanism.
issue creation with field validation and custom field mapping
Medium confidenceCreates new Jira issues via MCP tool endpoint, accepting issue type, summary, description, and optional custom fields. Validates required fields against Jira project schema before submission, maps caller-provided field names to Jira internal field IDs, and returns the created issue key and URL. Uses Jira REST API v3 issue creation endpoint with pre-flight schema validation.
Implements pre-flight schema validation and custom field ID mapping as part of the MCP tool, reducing caller burden of field ID lookup and validation; modular design allows custom field mappings to be configured per project
Safer than raw REST API calls because it validates fields before submission; more flexible than simple issue templates because it supports custom field mapping and dynamic field population
issue update and transition with workflow state management
Medium confidenceUpdates existing Jira issues via MCP tool endpoint, supporting field updates (summary, description, assignee, priority, custom fields) and workflow transitions (status changes). Queries available transitions for the current issue state, validates the requested transition is legal, and applies the transition with optional comment. Uses Jira REST API v3 issue update and transition endpoints.
Validates workflow transitions before applying them by querying available transitions from Jira, preventing illegal state changes and providing agents with visibility into valid next states; separates field updates from transitions for independent control
More robust than direct REST API calls because it validates transitions; more flexible than simple status-change tools because it supports arbitrary field updates and optional comments
user and team member querying with permission context
Medium confidenceQueries Jira Cloud user directory via MCP tool endpoint, returning user details (name, email, avatar, active status) and optionally filtering by project or board membership. Uses Jira REST API v3 user search endpoint with optional permission filters to identify assignable users for a given project. Caches user list in memory to reduce API calls for repeated queries.
Implements in-memory user caching to reduce API calls for repeated user queries, with optional permission filtering to return only assignable users for a project; modular design allows cache invalidation strategies to be plugged in
Faster than raw user search API calls due to caching; more contextual than generic user directories because it filters by project permissions
comment creation and retrieval with thread context
Medium confidenceCreates comments on Jira issues and retrieves existing comments via MCP tool endpoints. Comment creation supports plain text and optional Jira markup formatting. Comment retrieval returns paginated comment history with author, timestamp, and edit history. Uses Jira REST API v3 comment endpoints with optional visibility restrictions (public vs. restricted to specific groups).
Supports both comment creation and retrieval through unified MCP tool endpoints, with optional visibility restrictions for sensitive comments; integrates comment history into agent context for decision-making
More integrated than raw API calls because it handles Jira markup formatting; more flexible than simple logging because it supports visibility restrictions and comment history retrieval
sprint management and issue assignment to sprints
Medium confidenceQueries active and future sprints for a board, and assigns or moves issues between sprints via MCP tool endpoints. Sprint queries return sprint metadata (name, state, start/end dates, goal). Issue assignment uses Jira REST API v3 sprint endpoints to move issues atomically. Supports bulk sprint operations (move multiple issues to sprint in single call if Jira API supports it).
Provides unified MCP tool endpoints for both sprint querying and issue assignment, allowing agents to understand sprint state and make assignment decisions in a single interaction; modular design separates sprint metadata from issue operations
More integrated than raw API calls because it abstracts sprint state queries and issue assignment; more flexible than simple sprint assignment because it provides sprint metadata for decision-making
issue attachment upload and metadata retrieval
Medium confidenceUploads files as attachments to Jira issues and retrieves attachment metadata (filename, size, author, timestamp, download URL) via MCP tool endpoints. Supports common file types (images, documents, logs) with size validation. Uses Jira REST API v3 attachment endpoints with multipart form data for uploads. Attachment metadata includes direct download URLs for agent access.
Provides unified MCP tool endpoints for both attachment upload and metadata retrieval, with direct download URLs for agent access; handles multipart form data encoding transparently
More integrated than raw API calls because it handles file encoding and multipart form data; more flexible than simple file storage because it integrates attachments into Jira issue context
issue link creation and dependency tracking
Medium confidenceCreates links between Jira issues (e.g., 'blocks', 'relates to', 'duplicates') via MCP tool endpoint, enabling agents to model issue dependencies and relationships. Queries available link types for a project and validates link creation before submission. Uses Jira REST API v3 issue link endpoints. Supports bidirectional link creation (A blocks B automatically creates B is blocked by A).
Provides MCP tool endpoint for issue linking with automatic bidirectional link creation, allowing agents to model complex dependencies without manual reverse-link management; validates link types before submission
More integrated than raw API calls because it handles bidirectional link creation; more flexible than simple blocking relationships because it supports arbitrary link types
project and board discovery with schema introspection
Medium confidenceQueries available Jira projects and boards accessible to the authenticated user via MCP tool endpoints, returning project metadata (key, name, type, category) and board configuration (columns, swimlanes, issue types). Introspects project schema to discover custom fields, issue types, and available transitions. Uses Jira REST API v3 project and board endpoints with caching for schema data.
Implements schema introspection as a first-class MCP tool, allowing agents to discover project configuration dynamically without hardcoding; caches schema data to reduce API calls while providing cache invalidation hooks
More flexible than hardcoded project schemas because it discovers configuration at runtime; more efficient than repeated API calls because it caches schema data
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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mcp-atlassian
MCP server for Atlassian tools (Confluence, Jira)
Confluence MCP Server
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Best For
- ✓AI agents and LLM-based automation systems needing real-time Jira state
- ✓Teams building custom Jira dashboards or reporting integrations via Claude/LLM
- ✓Developers prototyping Jira-aware chatbots or task management bots
- ✓Agents needing to filter issues by multiple criteria (status, assignee, date range)
- ✓Automation workflows that must find and act on issues matching dynamic conditions
- ✓Teams building Jira-aware chatbots that answer 'show me all open bugs assigned to Alice'
- ✓Agents that need real-time visibility into Jira changes
- ✓Automation systems that react to issue events
Known Limitations
- ⚠Requires Jira Cloud instance (Server/Data Center not supported by Atlassian REST API v3)
- ⚠Board query returns only metadata; does not stream real-time updates or webhooks
- ⚠No built-in caching — each board query hits Jira API, risking rate limits under high-frequency agent calls
- ⚠JQL generation is manual or requires caller to provide JQL string; no natural language → JQL parser built-in
- ⚠Pagination requires explicit offset/limit parameters; no automatic cursor-based iteration
- ⚠Complex JQL queries (nested conditions, custom field logic) may require caller expertise
Requirements
Input / Output
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** A modular and extensible MCP server designed to interact with Jira Cloud, providing tools to query boards, issues, and user data — ideal for integrating Jira with AI agents, bots, or automation systems
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