Commit Graph
3 Commits
Author SHA1 Message Date
ClaudeandClaude Fable 5 627e70f697 feat: add fetch_url tool for proxying HTTP GET to cluster-internal URLs
Add a new MCP tool that lets the agent fetch URLs on the cluster's
network (YARN tracking UI, Spark History Server, NodeManager web UIs)
when the agent is on a different network and cannot reach those hosts
directly.

The MCP service runs on the YARN RM node, so it can reach every host
the cluster knows about — the agent just needs a way to ask.

Security: SSRF guard via host suffix overlap
  - URL host must share >= 2 labels of suffix with the named
    Connection's yarn_rm_url host (e.g. yarn_rm_url='rm.prod.internal'
    allows 'http://nm01.prod.internal/...')
  - IP literals (10.0.0.1, ::1) rejected
  - Non-http(s) schemes (file://, gopher://, ftp://) rejected
  - Connection with no yarn_rm_url cannot use this tool
- Reuses Connection.auth_for_httpx() and verify_for_httpx() so the
  agent does not need cluster credentials
- Response body capped at 1 MB (truncated=true if larger)
- 30s timeout, follows redirects, loguru INFO audit log on every call

- spark_executor/tools/fetch_url.py: new tool + 2 helpers
  (_host_suffix_overlap, _validate_url_host)
- spark_executor/models.py: FetchUrlResult Pydantic model
- spark_executor/tools/requests.py: FetchUrlRequest with descriptions
- spark_executor/server.py: /fetch_url route, operation_id='fetch_url'
- tests/unit/test_fetch_url.py: 13 unit tests covering all guards,
  truncation, auth/SSL pass-through, redirect follow
- tests/integration/test_mcp_routes.py: assert 21 tool routes
- README.md: 1 row in Spark Executor 工具 table

Tests: 369 passed (up from 356).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-09 10:59:25 +08:00
ClaudeandClaude Fable 5 6cf68439a2 feat: add external job tools + improve LLM-facing tool descriptions
Add 3 new MCP tools for inspecting YARN applications NOT submitted
through this service: get_external_job_logs, get_external_job_status,
get_external_job_result. Each takes application_id + connection_name
and queries YARN directly, bypassing the local JobStore.

- spark_executor/tools/external_jobs.py: 3 tool functions
- spark_executor/tools/requests.py: 3 new Pydantic body models
  (ExternalJobLogsRequest, ExternalJobStatusRequest,
  ExternalJobResultRequest)
- spark_executor/server.py: 3 new POST routes with explicit operation_id
- tests/unit/test_external_jobs.py: 7 unit tests
- tests/integration/test_mcp_routes.py: assert 20 tool routes
- README.md: list the 3 new tools

To make the LLM pick the right tool and not guess at field values,
also:

- Add Pydantic field descriptions for 22 fields across 8 request models
  (SaveConnectionRequest, UpdatePendingJobRequest, GetJobLogsRequest,
  JobIdRequest, PendingIdRequest, ConnectionNameRequest, plus the new
  ExternalJob*Request models).
- Update 12 route descriptions with cross-references, prerequisite
  context, and 400 behavior notes.
- Refactor _unknown_job_error: an input that looks like a YARN
  application_id (starts with 'application_') now returns HTTP 400
  (ValueError) with a hint message naming the right external tool;
  other not-found cases still return 404 (KeyError). This catches the
  common LLM mistake of passing application_id to the internal
  get_job_* / kill_job tools.
- 4 new unit tests for the 400 behavior.

Tests: 356 passed (up from 242).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-08 20:03:40 +08:00
Claude e285dc0f66 feat: add README.md 2026-07-02 12:17:27 +08:00