Incident Response MCP for Apache Airflow
PYPI · APACHE-AIRFLOW-MCP-SERVER · SCANNED SEP 20
Diagnose Airflow failures from UI links with bounded logs and optional recovery actions.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 2 of 19 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency35
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- License check failed: the license (Apache Software License) isn't a recognized OSI-approved license. See how to fix → Fail
- Actively maintained (last published 65 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability59
- AI-judged instruction clarity (good).Pass
- Context-footprint check failed: tool/resource definitions use about 3537 tokens (~221/item across 16 items; 16 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management83
- Stability observed for 25 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 16 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 17 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the Incident Response MCP for Apache Airflow server?
Incident Response MCP for Apache Airflow runs locally as a PyPI package, launched with uvx apache-airflow-mcp-server. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · apache-airflow-mcp-server
claude mcp add madamak-apache-airflow-mcp-server -- uvx apache-airflow-mcp-server
{
"mcpServers": {
"madamak-apache-airflow-mcp-server": {
"command": "uvx",
"args": [
"apache-airflow-mcp-server"
]
}
}
} {
"servers": {
"madamak-apache-airflow-mcp-server": {
"command": "uvx",
"args": [
"apache-airflow-mcp-server"
]
}
}
} codex mcp add madamak-apache-airflow-mcp-server -- uvx apache-airflow-mcp-server
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"madamak-apache-airflow-mcp-server": {
"type": "local",
"command": [
"uvx",
"apache-airflow-mcp-server"
],
"enabled": true
}
}
} openclaw mcp add madamak-apache-airflow-mcp-server --command uvx --arg apache-airflow-mcp-server
mcp_servers:
madamak-apache-airflow-mcp-server:
command: "uvx"
args: ["apache-airflow-mcp-server"] {
"McpServers": {
"madamak-apache-airflow-mcp-server": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"apache-airflow-mcp-server"
]
}
}
} assistant mcp add madamak-apache-airflow-mcp-server -t stdio -c uvx -a apache-airflow-mcp-server
{
"mcpServers": {
"madamak-apache-airflow-mcp-server": {
"command": "uvx",
"args": [
"apache-airflow-mcp-server"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 19 Sept 26 −2
- Stability: pass → 0.80 functional
- 18 Sept 26 0
- Stability: 0.97 → pass security
- 17 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 15 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 12 Sept 26 −2
- Stability: pass → 0.80 functional
- 11 Sept 26 0
- Stability: 0.97 → pass security
- 10 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 8 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 20 Sept 2026 · Analysed pypi/apache-airflow-mcp-server@1.0.2
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 19 packages
| Packages resolved | 19 |
|---|---|
| Stale | 2 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
airflow_clear_dag_run ~287
Destructively clear all task instances within one specific DAG run. Parameters - instance: Instance key (optional; mutually exclusive with ui_url) - ui_url: Airflow UI URL to resolve instance (optional; takes precedence) - dag_id: DAG identifier (required if ui_url not provided) - dag_run_id: DAG run identifier (required if ui_url not provided) - include_subdags: Include subDAGs (optional) - include_parentdag: Include parent DAG (optional) - include_upstream: Include upstream tasks (optional) - include_downstream: Include downstream tasks (optional) - dry_run: Preview without mutating (default true); set false explicitly to clear - reset_dag_runs: Reset DagRun state (optional) Returns - Response dict: { "dag_id": str, "dag_run_id": str, "cleared": object, "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| dag_id | – | – | – |
| dag_run_id | – | – | – |
| dry_run | – | – | – |
| include_downstream | – | – | – |
| include_parentdag | – | – | – |
| include_subdags | – | – | – |
| include_upstream | – | – | – |
| instance | – | – | – |
| reset_dag_runs | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_clear_task_instances ~356
Clear task instances for a DAG across one or more runs using Airflow's native filter set (destructive). Parameters - instance: Instance key (optional; mutually exclusive with ui_url) - ui_url: Airflow UI URL to resolve instance (optional; takes precedence) - dag_id: DAG identifier (required if ui_url not provided) - task_ids: List of task IDs to clear (optional) - start_date: ISO8601 start date filter (optional) - end_date: ISO8601 end date filter (optional) - include_subdags: Include subDAGs (optional) - include_parentdag: Include parent DAG (optional) - include_upstream: Include upstream tasks (optional) - include_downstream: Include downstream tasks (optional) - include_future: Include future runs (optional) - include_past: Include past runs (optional) - dry_run: Preview without mutating (default true); set false explicitly to clear - reset_dag_runs: Reset DagRun state (optional) Returns - Response dict: { "dag_id": str, "cleared": object, "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| dag_id | – | – | – |
| dry_run | – | – | – |
| end_date | – | – | – |
| include_downstream | – | – | – |
| include_future | – | – | – |
| include_parentdag | – | – | – |
| include_past | – | – | – |
| include_subdags | – | – | – |
| include_upstream | – | – | – |
| instance | – | – | – |
| reset_dag_runs | – | – | – |
| start_date | – | – | – |
| task_ids | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_dataset_events ~120
List dataset events. Parameters - instance: Instance key (optional) - ui_url: Airflow UI URL to resolve instance (optional) - dataset_uri: Dataset URI (required) - limit: Max results (default 50; accepts int/float/str, coerced to non-negative int, fractional values truncated) Returns - Response dict: { "events": [object], "count": int, "request_id": str }
| Name | Type | Req | Description |
|---|---|---|---|
| dataset_uri | – | – | – |
| instance | – | – | – |
| limit | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_describe_instance ~101
Describe a configured Airflow instance (host + metadata, never secrets). Parameters - instance: Instance key (e.g., "data-stg") Returns - Response dict: { "instance", "host", "api_version", "verify_ssl", "auth_type", "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| instance | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_get_dag ~119
Get DAG details and a UI link. Parameters - instance | ui_url: Provide one; `ui_url` auto-resolves/validates the host. - dag_id: Required when only `instance` is supplied. Returns - Response dict: { "dag": object, "ui_url": str, "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| dag_id | – | – | – |
| instance | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_get_dag_run ~115
Get a single DAG run and a UI link. Parameters - instance: Instance key (optional) - ui_url: Airflow UI URL to resolve instance/dag/dag_run (optional) - dag_id: DAG identifier - dag_run_id: DAG run identifier Returns - Response dict: { "dag_run": object, "ui_url": str, "request_id": str }
| Name | Type | Req | Description |
|---|---|---|---|
| dag_id | – | – | – |
| dag_run_id | – | – | – |
| instance | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_get_task_instance ~276
Return task metadata, config, attempt summary, optional rendered fields, and UI URLs. Parameters - instance | ui_url: Target selection (URL precedence) - dag_id, dag_run_id, task_id: Required identifiers (unless resolved from ui_url) - include_rendered: When true, include rendered template fields (truncated using max_rendered_bytes) - max_rendered_bytes: Byte cap for rendered fields payload (default 100KB; accepts int/float/str, coerced to positive int, fractional values truncated) Returns - Response dict: { "task_instance": {...}, "task_config": {...}, "attempts": {...}, "ui_url": {...}, "request_id": str, "rendered_fields"?: {...} } Notes - `attempts.try_number` is the authoritative input for `airflow_get_task_instance_logs`. - Rendered fields include `bytes_returned` and `truncated` metadata. - Sensors increment `try_number` on every reschedule, so treat it as an attempt index; the derived retries counters are heuristic.
| Name | Type | Req | Description |
|---|---|---|---|
| dag_id | – | – | – |
| dag_run_id | – | – | – |
| include_rendered | boolean | – | – |
| instance | – | – | – |
| max_rendered_bytes | – | – | – |
| task_id | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_get_task_instance_logs ~666
Fetch task instance logs with optional filtering and truncation. Large log handling: Logs >100MB automatically tail to last 10,000 lines (sets auto_tailed=true). Host-segmented responses are flattened into a single string using headers of the form `--- [worker] ---`, ensuring agents can reason about multi-host output. The tool requires an explicit `try_number`; callers should first retrieve it via `airflow_get_task_instance`. Filter order of operations: 1. Auto-tail: If log >100MB, take last 10,000 lines 2. tail_lines: Extract last N lines from log 3. filter_level: Find matching lines by level (content filter) 4. context_lines: Add surrounding lines around matches (symmetric: N before + N after) 5. max_bytes: Hard cap on total output (UTF-8 safe truncation) Parameters - instance: Instance key (optional, mutually exclusive with ui_url) - ui_url: Airflow UI URL to resolve identifiers (optional) - dag_id, dag_run_id, task_id, try_number: Task instance identifiers (required) - filter_level: "error" | "warning" | "info" (optional) - Show only lines matching level * "error": ERROR, CRITICAL, FATAL, Exception, Traceback * "warning": WARN, WARNING + error patterns * "info": INFO + warning + error patterns - context_lines: N lines before/after each match (optional, clamped to [0, 1000]; accepts int/float/str, coerced to non-negative int, fractional values truncated) - tail_lines: Extract last N lines before filtering (optional, clamped to [0, 100000]; accepts int/float/str, coerced to non-negative int, fractional values truncated) - max_bytes: Maximum response size in bytes (default: 100KB ≈ 25K tokens, clamped to 1MB) Returns - Response dict with fields: * log: Normalized/filtered log text (host headers inserted when needed) * truncated: true if output exceeded max_bytes * auto_tailed: true if original log >100MB triggered auto-tail * bytes_returned: Actual byte size of returned log * original_lines: Line count before any filtering *…
| Name | Type | Req | Description |
|---|---|---|---|
| context_lines | – | – | – |
| dag_id | – | – | – |
| dag_run_id | – | – | – |
| filter_level | – | – | – |
| instance | – | – | – |
| max_bytes | integer | – | – |
| tail_lines | – | – | – |
| task_id | – | – | – |
| try_number | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_list_dag_runs ~325
List DAG runs (defaults to execution_date DESC) with per-run UI URLs. Parameters - instance: Instance key (optional) - ui_url: Airflow UI URL to resolve instance/dag_id (optional) - dag_id: DAG identifier (required if ui_url not provided) - limit: Max results (default 100; accepts int/float/str, coerced to non-negative int, fractional values truncated) - offset: Offset for pagination (default 0; accepts int/float/str, coerced to non-negative int, fractional values truncated) - state: List of states to filter by (optional) - order_by: Optional `"start_date"`, `"end_date"`, `"execution_date"`, or `"logical_date"` (omit to use ``execution_date``; execution_date and logical_date are mapped to whichever name the target Airflow version uses) - descending: Sort direction (default True). Ignored when order_by is omitted; defaults always use execution_date descending Returns - Response dict: { "dag_runs": [{ "dag_run_id", "state", "start_date", "end_date", "ui_url" }], "count": int, "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| dag_id | – | – | – |
| descending | boolean | – | – |
| instance | – | – | – |
| limit | – | – | – |
| offset | – | – | – |
| order_by | – | – | – |
| state | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_list_dags ~203
List DAGs (pause state + UI link) for the target instance. Parameters - instance: Instance key (optional; mutually exclusive with ui_url) - ui_url: Airflow UI URL to resolve instance (optional; takes precedence - must match a configured host) - limit: Max results (default 100; accepts int/float/str, coerced to non-negative int, fractional values truncated) - offset: Offset for pagination (default 0; accepts int/float/str, coerced to non-negative int, fractional values truncated) Returns - Response dict: { "dags": [{ "dag_id", "is_paused", "ui_url" }], "count": int, "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| instance | – | – | – |
| limit | – | – | – |
| offset | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_list_instances ~66
List configured Airflow instance keys. Returns - Response dict: { "instances": [str], "default_instance": str | null, "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
airflow_list_task_instances ~298
List task instances within one DAG run, including state and attempt log URLs. Parameters - instance: Instance key (optional) - ui_url: Airflow UI URL to resolve instance/dag/dag_run (optional) - dag_id: DAG identifier - dag_run_id: DAG run identifier - limit: Max results (default 100; accepts int/float/str, coerced to non-negative int, fractional values truncated) - offset: Offset for pagination (default 0; accepts int/float/str, coerced to non-negative int, fractional values truncated) - state: Optional list of task states (case-insensitive). When provided, only matching states are returned. - task_ids: Optional list of task identifiers to include. Returns - Response dict: { "task_instances": [{ "task_id", "state", "try_number", "ui_url" }], "count": int, "total_entries"?: int, "filters"?: { "state": [...], "task_ids": [...] }, "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| dag_id | – | – | – |
| dag_run_id | – | – | – |
| instance | – | – | – |
| limit | – | – | – |
| offset | – | – | – |
| state | – | – | – |
| task_ids | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_pause_dag ~145
Pause DAG scheduling (sets `is_paused=True` and returns UI link). Parameters - instance: Instance key (optional; mutually exclusive with ui_url) - ui_url: Airflow UI URL to resolve instance (optional; takes precedence) - dag_id: DAG identifier (required if ui_url not provided) Returns - Response dict: { "dag_id": str, "is_paused": true, "ui_url": str, "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| dag_id | – | – | – |
| instance | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_resolve_url ~105
Parse an Airflow UI URL, resolve instance and identifiers. Parameters - url: Airflow UI URL (http/https) Returns - Response dict: { "instance", "dag_id"?, "dag_run_id"?, "task_id"?, "try_number"?, "route", "request_id" } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| url | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_trigger_dag ~198
Trigger a DAG run with optional configuration. Parameters - instance: Instance key (optional; mutually exclusive with ui_url) - ui_url: Airflow UI URL to resolve instance (optional; takes precedence) - dag_id: DAG identifier (required if ui_url not provided) - dag_run_id: Custom run id (optional) - logical_date: Optional ISO8601 logical date/time assigned to the new run - conf: Configuration object as dict or JSON string (optional) - note: Run note/comment (optional) Returns - Response dict: { "dag_run_id": str, "ui_url": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| conf | – | – | – |
| dag_id | – | – | – |
| dag_run_id | – | – | – |
| instance | – | – | – |
| logical_date | – | – | – |
| note | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
airflow_unpause_dag ~146
Resume DAG scheduling (sets `is_paused=False` and returns UI link). Parameters - instance: Instance key (optional; mutually exclusive with ui_url) - ui_url: Airflow UI URL to resolve instance (optional; takes precedence) - dag_id: DAG identifier (required if ui_url not provided) Returns - Response dict: { "dag_id": str, "is_paused": false, "ui_url": str, "request_id": str } - Raises: ToolError with compact JSON payload (`code`, `message`, `request_id`, optional `context`)
| Name | Type | Req | Description |
|---|---|---|---|
| dag_id | – | – | – |
| instance | – | – | – |
| ui_url | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
What is the Incident Response MCP for Apache Airflow server?
Incident Response MCP for Apache Airflow is listed in the public MCP registry as io.github.madamak/apache-airflow-mcp-server. Diagnose Airflow failures from UI links with bounded logs and optional recovery actions. This page covers its PyPI package (apache-airflow-mcp-server).
Is the Incident Response MCP for Apache Airflow server safe to use?
Incident Response MCP for Apache Airflow scores 75 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Incident Response MCP for Apache Airflow server expose?
Incident Response MCP for Apache Airflow exposes 16 tools: airflow_list_instances, airflow_describe_instance, airflow_resolve_url, airflow_list_dags, airflow_get_dag, and 11 more. Their descriptions and schemas cost roughly 3,526 tokens of context every time the server is loaded.
Is the Incident Response MCP for Apache Airflow server still maintained?
Incident Response MCP for Apache Airflow is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.