Jira MCP Server

An MCP server for accessing JIRA issue data stored in Snowflake.

A Model Context Protocol (MCP) server that provides access to JIRA issue data stored in Snowflake. This server enables AI assistants to query, filter, and analyze JIRA issues through a standardized interface.

This MCP server connects to Snowflake to query JIRA data and provides five main tools for interacting with the data:

- list_jira_issues- Query and filter JIRA issues with various criteria
- get_jira_issue_details- Get detailed information for multiple issues by their keys
- get_jira_project_summary- Get statistics and summaries for all projects
- get_jira_issue_links- Get issue links for a specific JIRA issue by its key
- get_jira_issues_by_sprint- Get all JIRA issues in a specific sprint by sprint name

The server connects to Snowflake and queries the following tables:

- JIRA_ISSUE_NON_PII- Main issue data (non-personally identifiable information)
- JIRA_LABEL_RHAI- Issue labels and tags
- JIRA_COMMENT_NON_PII- Issue comments (non-personally identifiable information)
- JIRA_COMPONENT_RHAI- JIRA project components and their metadata
- JIRA_NODEASSOCIATION_RHAI- Associations between JIRA entities (issues, components, versions)
- JIRA_PROJECTVERSION_NON_PII- Project versions (fix versions and affected versions)
- JIRA_ISSUELINK_RHAI- Links between JIRA issues
- JIRA_ISSUELINKTYPE_RHAI- Types of issue links
- JIRA_CUSTOMFIELDVALUE_NON_PII- Custom field values (e.g., sprint information)
- JIRA_SPRINT_RHAI- Sprint data
- JIRA_CHANGEGROUP_RHAI- Change history groups
- JIRA_CHANGEITEM_RHAI- Individual change items (e.g., status changes)

Note: Table names are expected to exist in your configured Snowflake database and schema.

Query JIRA issues with optional filtering:

- Project filtering- Filter by project key (e.g., 'SMQE', 'OSIM')
- Issue keys filtering- Filter by specific issue keys (e.g., ['SMQE-1280', 'SMQE-1281'])
- Issue type filtering- Filter by issue type ID
- Status filtering- Filter by issue status ID
- Priority filtering- Filter by priority ID
- Text search- Search in summary and description fields
- Component filtering- Filter by component names (comma-separated, matches any)
- Version filtering- Filter by fixed version or affected version name
- Date filtering- Filter by creation, update, or resolution date within last N days
- Timeframe filtering- Filter issues where any date (created, updated, or resolved) is within last N days
- Result limiting- Control number of results returned (default: 50)

- Basic issue information (summary, description, status, priority)
- Timestamps (created, updated, due date, resolution date)
- Metadata (votes, watches, environment, components)
- Associated labels and links
- Fixed and affected versions

2. Get Issue Details (get_jira_issue_details)

Retrieve comprehensive information for multiple JIRA issues by their keys (e.g., ['SMQE-1280', 'SMQE-1281']), including:

- Basic issue information (summary, description, status, priority)
- Timestamps (created, updated, due date, resolution date)
- Time tracking (original estimate, current estimate, time spent)
- Metadata (votes, watches, environment, components, workflow ID, security, archived status)
- Associated labels
- Comments (with comment body, creation/update timestamps, and role level)
- Issue links (inward and outward)
- Status change history
- Fixed and affected versions

- found_issues- Dictionary of found issues keyed by issue key
- not_found- List of issue keys that were not found
- total_found- Number of issues found
- total_requested- Number of issues requested

3. Get Project Summary (get_jira_project_summary)

Generate statistics across all projects:

- Total issue counts per project
- Status distribution per project
- Priority distribution per project
- Overall statistics

4. Get Issue Links (get_jira_issue_links)

Get issue links for a specific JIRA issue by its key (e.g., 'SMQE-1280'):

- Issue links- Relationships to other issues (blocks, is blocked by, relates to, etc.)
- Link direction- Indicates if the link is inward or outward
- Linked issue details- Information about the linked issue

- Issue key and ID
- List of all issue links with link type and direction
- Total count of links

5. Get Issues by Sprint (get_jira_issues_by_sprint)

Get all JIRA issues in a specific sprint by sprint name:

- Sprint filtering- Filter by sprint name (e.g., 'Sprint 256')
- Project filtering- Optional filter by project key (e.g., 'SMQE', 'OSIM')
- Result limiting- Control number of results returned (default: 50)

- All standard issue fields (same aslist_jira_issues)
- Sprint ID and sprint name
- Associated labels and links
- Fixed and affected versions

The server includes optional Prometheus metrics support for monitoring:

- Tool usage tracking- Track calls to each MCP tool with success/error rates and duration
- Snowflake query monitoring- Monitor database query performance and success rates
- Connection tracking- Track active MCP connections
- HTTP endpoints-/metricsfor Prometheus scraping and/healthfor health checks

- Python 3.10+
- UV(Python package manager)
- Podman or Docker
- Access to Snowflake with appropriate credentials

# Generate private key openssl genrsa 2048 | openssl pkcs8 -topk8 -inform PEM -out rsa_key.p8 # Generate public key openssl rsa -in rsa_key.p8 -pubout -out rsa_key.pub

ALTER USER your_service_account SET RSA_PUBLIC_KEY='MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEA...';

export SNOWFLAKE_CONNECTION_METHOD=connector export SNOWFLAKE_AUTHENTICATOR=snowflake_jwt export SNOWFLAKE_ACCOUNT=your-account.snowflakecomputing.com export SNOWFLAKE_USER=your_service_account export SNOWFLAKE_PRIVATE_KEY_FILE=/path/to/rsa_key.p8 export SNOWFLAKE_DATABASE=your_database export SNOWFLAKE_SCHEMA=your_schema export SNOWFLAKE_WAREHOUSE=your_warehouse export SNOWFLAKE_ROLE=your_role

git clone <repository-url> cd jira-mcp-snowflake

# On macOS/Linux curl -LsSf https://astral.sh/uv/install.sh | sh # On Windows powershell -c "irm https://astral.sh/uv/install.ps1 | iex" # Or via pip pip install uv

# Install dependencies including dev packages make uv_sync_dev

# Run linting (flake8) make lint # Run tests with coverage make pytest # Run both linting and tests make test

# Build container image with Podman make build

podman build -t localhost/jira-mcp-snowflake:latest .

{ "mcpServers": { "jira-mcp-snowflake": { "command": "podman", "args": [ "run", "-i", "--rm", "-e", "SNOWFLAKE_CONNECTION_METHOD=api", "-e", "SNOWFLAKE_TOKEN=your_token_here", "-e", "SNOWFLAKE_BASE_URL=https://your-account.snowflakecomputing.com/api/v2", "-e", "SNOWFLAKE_DATABASE=your_database_name", "-e", "SNOWFLAKE_SCHEMA=your_schema_name", "-e", "MCP_TRANSPORT=stdio", "-e", "ENABLE_METRICS=true", "-e", "METRICS_PORT=8000", "localhost/jira-mcp-snowflake:latest" ] } } }

Example 2: Private Key Authentication (Service Account)

{ "mcpServers": { "jira-mcp-snowflake": { "command": "podman", "args": [ "run", "-i", "--rm", "-v", "/path/to/your/rsa_key.p8:/app/rsa_key.p8:ro", "-e", "SNOWFLAKE_CONNECTION_METHOD=connector", "-e", "SNOWFLAKE_AUTHENTICATOR=snowflake_jwt", "-e", "SNOWFLAKE_ACCOUNT=your-account.snowflakecomputing.com", "-e", "SNOWFLAKE_USER=your_service_account", "-e", "SNOWFLAKE_PRIVATE_KEY_FILE=/app/rsa_key.p8", "-e", "SNOWFLAKE_DATABASE=your_database_name", "-e", "SNOWFLAKE_SCHEMA=your_schema_name", "-e", "SNOWFLAKE_WAREHOUSE=your_warehouse_name", "-e", "SNOWFLAKE_ROLE=your_role_name", "-e", "MCP_TRANSPORT=stdio", "-e", "ENABLE_METRICS=true", "-e", "METRICS_PORT=8000", "localhost/jira-mcp-snowflake:latest" ] } } }

Then access metrics at:http://localhost:8000/metrics

Example configuration for connecting to a remote instance:

{ "mcpServers": { "jira-mcp-snowflake": { "url": "https://jira-mcp-snowflake.example.com/sse", "headers": { "X-Snowflake-Token": "your_token_here" } } } }

Example configuration to add to VS Code Continue:

{ "experimental": { "modelContextProtocolServers": [ { "name": "jira-mcp-snowflake", "transport": { "type": "stdio", "command": "podman", "args": [ "run", "-i", "--rm", "-e", "SNOWFLAKE_TOKEN=your_token_here", "-e", "SNOWFLAKE_BASE_URL=https://your-account.snowflakecomputing.com/api/v2", "-e", "SNOWFLAKE_DATABASE=your_database_name", "-e", "SNOWFLAKE_SCHEMA=your_schema_name", "-e", "MCP_TRANSPORT=stdio", "-e", "ENABLE_METRICS=true", "-e", "METRICS_PORT=8000", "localhost/jira-mcp-snowflake:latest" ] } } ] } }

# List all issues from the SMQE project result = await list_jira_issues(project="SMQE", limit=10)

# Search for issues containing "authentication" in summary or description result = await list_jira_issues(search_text="authentication", limit=20)

# Find issues in specific components result = await list_jira_issues(components="Security,Authentication", limit=20)

# Find issues with a specific fixed version result = await list_jira_issues(fixed_version="2.5.0", limit=20)

# Find issues created in the last 7 days result = await list_jira_issues(created_days=7, limit=20) # Find issues updated in the last 30 days result = await list_jira_issues(updated_days=30, limit=50)

# Get detailed information for multiple issues result = await get_jira_issue_details(issue_keys=["SMQE-1280", "SMQE-1281"]) # Access the results for issue_key, issue_data in result["found_issues"].items(): print(f"Issue: {issue_key}") print(f"Summary: {issue_data['summary']}") print(f"Status: {issue_data['status']}") print(f"Labels: {issue_data['labels']}") print(f"Comments: {len(issue_data['comments'])}")

# Get all issue links for a specific issue result = await get_jira_issue_links(issue_key="SMQE-1280") # Access the links print(f"Total links: {result['total_links']}") for link in result['links']: print(f"Link type: {link['link_type']}") print(f"Direction: {link['direction']}") print(f"Linked issue: {link['linked_issue_key']}")

# Get all issues in a specific sprint result = await get_jira_issues_by_sprint(sprint_name="Sprint 256", limit=50) # Get issues in a sprint for a specific project result = await get_jira_issues_by_sprint( sprint_name="Sprint 256", project="SMQE", limit=50 ) # Access the results print(f"Sprint: {result['sprint_name']}") print(f"Total issues: {result['total_returned']}") for issue in result['issues']: print(f"Issue: {issue['key']} - {issue['summary']}") print(f"Status: {issue['status']}")

# Get statistics for all projects result = await get_jira_project_summary()

When metrics are enabled, the server provides the following monitoring endpoints: