jira-pm-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@jira-pm-mcpget sprint health for PROJ Sprint 5"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
jira-pm-mcp
An MCP server that wraps the JIRA Cloud REST API for AI-driven agile project management. Designed to be run as a daily batch by an AI agent (e.g. via OpenClaw) to monitor sprint health, sync labels, flag risks, and write audit receipts.
Requirements
Node.js 20+
JIRA Cloud instance
API token with edit-issues and add-comments permissions on the target projects
Related MCP server: Jira MCP Integration
Setup
npm install
npm run buildEnvironment variables
Variable | Required | Description |
| yes | Base URL of your JIRA instance (e.g. |
| yes | Email address tied to the API token |
| yes | JIRA Cloud API token |
| no | When set, starts an HTTP/SSE server on this port instead of stdio |
Transport modes
The server supports two transport modes selected at startup.
stdio (default)
The server process is spawned and managed by the MCP client. Env vars are passed through the client config. Best for local single-user setups.
{
"mcpServers": {
"jira-pm": {
"command": "node",
"args": ["/path/to/jira-pm-mcp/dist/index.js"],
"env": {
"JIRA_BASE_URL": "https://yourcompany.atlassian.net",
"JIRA_EMAIL": "you@company.com",
"JIRA_API_TOKEN": "your-token"
}
}
}
}HTTP/SSE
The server runs as a persistent HTTP process. The MCP client connects to it via SSE. Best for running the server as a system service or Docker container shared across multiple clients.
Start the server:
export JIRA_BASE_URL=https://yourcompany.atlassian.net
export JIRA_EMAIL=you@company.com
export JIRA_API_TOKEN=your-token
export PORT=3000
node dist/index.jsClaude Desktop config (claude_desktop_config.json):
{
"mcpServers": {
"jira-pm": {
"url": "http://localhost:3000/sse"
}
}
}Endpoints:
Endpoint | Method | Description |
| GET | SSE stream — MCP client connects here |
| POST | MCP message delivery (used internally by client) |
| GET | Liveness probe — returns |
Tools
setup_project
Configure a project for PM Agent monitoring. Must be run before any other tools. Validates connectivity and write permissions, then stores configuration as a YAML comment on the Root Epic and registers the project locally.
Parameter | Type | Required | Description |
| string | yes | JIRA project key (e.g. |
| string | yes | Key of the root epic that parents all cross-project tasks (e.g. |
| number | no | JIRA board ID (optional, for validation only) |
| string | no | JQL field for child tasks. |
| string[] | no | Status names that count as in-progress. Default: |
| string | no | Project delivery deadline |
| string | no | Custom field key for story points. Default: |
Returns: A checklist of validation results (root_epic, fix_versions, write_permissions, config_written) plus the config comment ID.
list_projects
List all projects registered with the PM Agent, with their configuration summary.
No parameters.
Returns: Array of projects with project_key, root_epic_key, committed_date, epic_link_field, active_statuses, and config_available.
list_fix_versions
List all fixVersions (sprints) for a project. Identifies the currently active sprint and how far through it we are.
Parameter | Type | Required | Description |
| string | yes | JIRA project key |
Returns: Array of versions with name, label_equivalent (spaces replaced with hyphens), start_date, release_date, is_active, is_released, and elapsed_pct.
get_sprint_health
Read-only full sprint health snapshot. Builds the full dependency graph — stories → blocking tasks → dates and status — without making any changes to JIRA. Safe to call at any time.
Parameter | Type | Required | Description |
| string | yes | JIRA project key |
| string | yes | fixVersion name identifying the sprint |
Returns:
Sprint metadata (dates,
elapsed_pct,committed_date)Summary counts (
total_stories,stories_with_no_tasks,stories_past_sprint_end,tasks_missing_dates,orphaned_tasks)Per-story breakdown:
effective_completion_date(max end date across blocking tasks),past_sprint_end,past_committed_date,has_date_gap, and the full list of blocking tasks with their dates, assignees, and currentpm-*labelsorphaned_tasks: tasks under the root epic that don't block any story in this sprint
run_sprint_audit
Run the daily PM audit for a sprint. This is the main write tool — it applies all label and date changes to JIRA and writes an audit receipt to the Root Epic.
Parameter | Type | Required | Description |
| string | yes | JIRA project key |
| string | yes | fixVersion name identifying the sprint |
| boolean | no | If |
What it does (in order):
Sync sprint labels — adds the sprint label (fixVersion with spaces → hyphens) to all blocking tasks in the sprint
Compute task flags — evaluates each blocking task and applies
pm-flag-*labels:Date slip: end date past sprint boundary (
pm-flag-critical-date-slip,pm-flag-warn-date-approaching)Commitment risk: end date past
committed_date(pm-flag-task-beyond-commitment)Not started: task in Backlog/Todo at mid-sprint (
pm-flag-critical-not-started,pm-flag-warn-not-started)Stalled: no status change for more than
stalled_threshold_days(pm-flag-warn-stalled)
Compute story flags — evaluates each story:
Stories whose
effective_completion_dateslips past the sprint end orcommitted_date(pm-flag-story-at-risk,pm-flag-story-beyond-commitment)Stories with missing blocking tasks (
pm-flag-missing-tasks)Stories with date gaps between blocking tasks (
pm-flag-date-gap)Stories recommended for deferral (
pm-flag-recommend-defer)
Update story due dates — sets each story's
duedateto itseffective_completion_date(max end date of blocking tasks)Velocity calculation — if
committed_dateis set, samples up to 5 past released sprints, computes average velocity, and projects expected completion dateWrite audit receipt — posts a YAML receipt comment to the Root Epic
Tasks with pm-acknowledged are skipped entirely (human override).
Returns: Summary of changes made, label_changes, story_date_changes, tasks_needing_dates, defer_recommendations, velocity result, and receipt_comment_id.
rollback_audit
Reverse the label and story date changes made by a previous run_sprint_audit. Reads the audit receipt from the Root Epic and applies the inverse diff. Never removes pm-acknowledged labels.
Parameter | Type | Required | Description |
| string | yes | JIRA project key |
| string | no | Timestamp from the receipt to roll back (e.g. |
Returns: rolled_back_audit, changes_reversed, errors, and rollback_receipt_comment_id.
search_issues
Escape hatch for ad-hoc JQL queries. Returns a page of matching issues with key, summary, status, assignee, labels, fixVersions, and due date. Use the high-level tools (get_sprint_health, run_sprint_audit) for routine PM operations.
Parameter | Type | Required | Description |
| string | yes | JQL query string |
| number | no | Pagination offset (default: |
| number | no | Results per page, max 100 (default: |
| string[] | no | Specific field keys to return |
Returns: total, start_at, max_results, returned, and issues array.
pm-* label taxonomy
The agent owns the full pm-* label namespace. All managed labels are cleared and recomputed on each audit run. The one exception is pm-acknowledged — set by a human to suppress all agent flags on that issue; the agent never removes it.
Label | Applied to | Meaning |
| Task or Story | Human override — agent skips this issue entirely |
| Task | End date is past the sprint boundary |
| Task | End date is within the last 20% of the sprint |
| Task | End date is past |
| Task | Still in Backlog/Todo past the 50% sprint mark |
| Task | Still in Backlog/Todo past the 25% sprint mark |
| Task | No status change for more than |
| Task | Task blocks stories in multiple projects |
| Story |
|
| Story |
|
| Story | Velocity projection shows project won't meet |
| Story | Story has no blocking tasks linked |
| Story | Gap exists between consecutive blocking task date windows |
| Story | Story is unlikely to complete in time; defer recommended |
Sprint labels (e.g. SIT-27-02-2026) are also applied to blocking tasks by the audit — these are derived from fixVersion names with spaces replaced by hyphens.
Authority model
Action | Who |
Set task start/end dates | Human only |
Set story due date | PM Agent (auto-set to |
Add/remove | PM Agent |
Add sprint label to tasks | PM Agent |
Add | Human only |
Remove | Human only |
Create fixVersions | Human only |
Sprint planning (assign stories to fixVersion) | Human only |
Architecture
src/
server.ts — MCP server entry point, registers all tools
tools/ — One file per MCP tool
jira/ — JIRA REST API client wrappers (client, search, issues, versions, comments)
audit/ — Core audit logic (graph, flags, velocity, receipt)
config/ — Project config schema, JIRA-backed storage, local registry
utils/ — Labels, dates, JQL builderConfiguration is stored as a YAML comment on the Root Epic in JIRA (prefixed with ## pm-agent-config), making it portable and version-controlled alongside the project. A local .jira-pm-registry.json maps project_key → root_epic_key to bootstrap config reads without a prior JIRA call.
Available Tools
4 toolsrun_sprint_auditA
Run the daily PM audit for a sprint. Syncs sprint labels on blocking tasks, computes and applies pm-* risk flags, auto-updates story due dates to effective_completion_date, calculates velocity if committed_date is configured, and writes an audit receipt to the Root Epic. Supports dry_run mode.
| Name | Required | Description | Default |
|---|---|---|---|
| dry_run | No | If true, compute all changes but do not write to JIRA | |
| fix_version | Yes | fixVersion name identifying the sprint | |
| project_key | Yes | JIRA project key |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It details the entire workflow: syncing labels, computing risk flags, updating due dates, calculating velocity if certain conditions are met, writing a receipt, and supporting a dry_run mode. This is comprehensive, though it could mention destructiveness or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences: the first defines the tool's core purpose, and the second enumerates specific actions. Every phrase contributes essential information, with no wasted words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description covers the actions, it lacks details about return values (no output schema) and error conditions. Prerequisites like project setup are not mentioned, but the sibling tools list includes setup_project, hinting at dependencies. The description is adequate for a daily audit tool but leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have full schema descriptions (100% coverage), so baseline is 3. The description adds value by explaining the effect of dry_run ('compute but do not write') and contextualizing fix_version as the sprint identifier. This enriches understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a daily PM audit for a sprint, listing specific actions like syncing labels, computing risk flags, updating due dates, calculating velocity, and writing an audit receipt. This specificity distinguishes it from sibling tools such as sync_sprint_tasks, which likely focus on task-level operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a daily usage context but does not explicitly state when to use this tool versus alternatives like sync_sprint_tasks or search_issues. No explicit exclusions or alternative recommendations are provided, though the 'daily PM audit' framing offers some guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_issuesA
Escape hatch for ad-hoc JQL queries. Returns a page of matching issues with key, summary, status, assignee, labels, and fixVersions. Use high-level tools (get_sprint_health, run_sprint_audit) for routine PM operations.
| Name | Required | Description | Default |
|---|---|---|---|
| jql | Yes | JQL query string | |
| fields | No | Specific field keys to return. Defaults to common fields. | |
| start_at | No | Pagination offset | |
| max_results | No | Results per page (max 100) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes return behavior (a page of matching issues with specific fields) but doesn't disclose pagination details, side effects, or auth requirements beyond what schema implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences only: first states purpose and output, second gives usage guidance. No wasted words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters and no output schema, the description covers purpose, return fields, and usage context. It lacks examples or JQL syntax guidance, but is sufficient for ad-hoc queries.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions for all 4 parameters. The description adds no additional parameter details beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it's an 'Escape hatch for ad-hoc JQL queries,' specifying the verb (search) and resource (issues). It lists return fields and distinguishes from high-level tools like get_sprint_health and run_sprint_audit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (ad-hoc JQL queries) and when not (use high-level tools for routine PM operations). Names two alternatives, providing clear context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
setup_projectA
Configure a project for PM Agent monitoring. Validates the root epic, board, fixVersions, and write permissions. Stores config as a YAML comment on the Root Epic. Must be run before any audit tools.
| Name | Required | Description | Default |
|---|---|---|---|
| board_id | No | JIRA board ID (optional) | |
| project_key | Yes | JIRA project key (e.g. PROJ) | |
| root_epic_key | Yes | Key of the root epic that parents all cross-project tasks (e.g. PROJ-1) | |
| committed_date | No | Optional project delivery deadline (YYYY-MM-DD). Enables delivery risk and velocity checks. | |
| active_statuses | No | Status names that mean work is actively in progress. Defaults to: In Progress, In Review, Code Review, In Testing. | |
| epic_link_field | No | JQL field for finding child tasks. setup_project will auto-detect the working field by probing JIRA — candidates tried in order: provided value → parentEpic → parent. | Epic Link |
| story_points_field | No | JIRA custom field key for story points. | customfield_10016 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses validation actions and config storage as a YAML comment. However, it does not describe error handling, side effects, or return behavior, leaving some behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences. The first sentence states the core purpose, the second details actions and requirements. No unnecessary information; front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters and no output schema, the description covers core behavior but omits return values and error scenarios. For a configuration tool, understanding success/failure conditions is important, so completeness is adequate but not outstanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining that parameters are validated and config is stored as a YAML comment, which goes beyond schema descriptions. This enhances understanding of how parameters are used.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Configure a project for PM Agent monitoring.' It details specific actions (validates root epic, board, fixVersions, write permissions) and distinguishes from sibling tools like run_sprint_audit by noting it is a setup prerequisite.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states 'Must be run before any audit tools,' providing clear when-to-use guidance. While it does not mention when-not-to-use or alternatives, the prerequisite nature is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sync_sprint_tasksA
Sync blocking task priorities and sprint labels to match user stories in a sprint. For each story in the sprint, finds all blocking Tasks and: (1) upgrades task priority if lower than the story priority, (2) adds the sprint label if missing. Excludes tasks with "SIT" or "UAT" in their summary. Supports resumable execution via a temp state file.
| Name | Required | Description | Default |
|---|---|---|---|
| sprint_name | Yes | fixVersion name identifying the sprint (e.g. "SIT-20/03/2026") | |
| project_keys | Yes | List of JIRA project keys to search for stories |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses key behaviors: it modifies priorities (upgrades if lower), adds sprint labels, excludes tasks with 'SIT' or 'UAT', and supports resumable execution via a temp state file. This provides good transparency, though it could mention potential side effects or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, each earning its place: purpose, action details, exclusion and resumability. It is front-loaded with the primary goal and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multi-step sync, no output schema, no annotations), the description covers the main behaviors, exclusions, and resumable execution. It is mostly complete, though missing details on error handling or idempotency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters with 100% coverage (sprint_name as fixVersion name, project_keys as JIRA project keys). The description adds overall context but does not provide additional parameter-level detail beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb and resource: 'Sync blocking task priorities and sprint labels to match user stories in a sprint.' It details the actions (upgrade priority, add label) and exclusions, making the purpose unambiguous and distinct from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the context (syncing tasks within a sprint) and what the tool does step-by-step, but it does not explicitly state when to use this tool versus alternatives like run_sprint_audit or search_issues. The usage is implied but not contrasted with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
4 tool updates
v1.0.0- First observed
run_sprint_audit - First observed
search_issues - First observed
setup_project - First observed
sync_sprint_tasks
TDQS
Each tool has a clearly distinct purpose: setup_project for configuration, run_sprint_audit for comprehensive sprint audit, sync_sprint_tasks for blocking task synchronization, and search_issues as an ad-hoc JQL escape hatch. No two tools overlap in functionality.
All tool names follow a consistent verb_noun pattern using snake_case (setup_project, run_sprint_audit, sync_sprint_tasks, search_issues), making the naming predictable and easy to understand.
With 4 tools, the server is well-scoped for its purpose as a PM monitoring assistant. Each tool serves a necessary function (setup, audit, sync, search), and the count fits comfortably within the typical 3-15 range.
The tool set covers the core PM workflow: configuration, audit, task synchronization, and ad-hoc queries. However, it references a 'get_sprint_health' tool that is not provided, and lacks tools for direct issue creation or manual updates, leaving minor gaps.
Maintenance
Resources
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