tao.chenandClaude df9b01272f admin: uploads list view with search, sort, and delete
Add /admin/uploads HTML page and JSON API backed by the upload_files

DB index. The page lists file_id, name, size (KB), uploaded_at, and

sha256 with client-side search by name, column sort, and per-row delete.

DELETE /admin/uploads/:id removes the DB index row and the on-disk

data file plus .meta.json sidecar. Admin deletes are written to the

audit log.

Wire the new dependencies through admin.Mount and main.go, and run

the backfill step on startup so pre-existing sidecars are indexed.

Tests cover auth, HTML rendering, JSON search, delete removing all

artifacts, and audit entry creation.

Co-Authored-By: Claude <noreply@anthropic.com>
2026-07-14 11:39:56 +08:00

spark-mcp-go

MCP (Model Context Protocol) server for Apache Spark on YARN. Lets an LLM agent discover Spark/YARN endpoints, submit jobs, fetch logs, and analyze them via 11 typed Tools. Streamable HTTP transport, SQLite-backed configuration, and log/slog structured logging with per-Tool call files.

What it does

  • Exposes 11 MCP Tools over Streamable HTTP at /mcp
  • Admin API at /admin/* for cluster and audit configuration
  • HTTP Basic and YARN SimpleAuth for Spark/YARN endpoints
  • SSRF protection with cluster URL allowlist plus DNS rebinding guard
  • Per-Tool independent audit log (file mode 0600)
  • spark-submit via local exec.Command (no shell, no injection)

Quick start (3 steps)

  1. Copy and edit the environment file:

    cp .env.example .env
    # Edit ADMIN_TOKENS and AGENT_TOKEN
    
  2. Build and start the server:

    go build ./...
    ./spark-mcp-go
    # Or use the helper:
    # ./scripts/dev.sh
    
  3. Initialize an MCP session, then call list_clusters to discover endpoints.

11 Tools

Tool Type Purpose
list_clusters discovery Return all active clusters (LLM entry point)
spark_submit exec Local spark-submit process, extracts app_id
list_applications RM GET /ws/v1/cluster/apps[?state=&user=]
get_application_status RM GET /ws/v1/cluster/apps/{id}
get_application_logs RM Fallback chain: amContainerLogs -> aggregated-logs -> logs
kill_application RM PUT state KILLED
fetch_spark_metrics SHS Executor metrics + summary mode triggers analyzer
fetch_cluster_env RM Aggregate /cluster/info and /cluster/metrics
analyze_spark_log analyzer RM logs + heuristic rules + LLM-ready prompt
fetch_url HTTP Generic primitive, uses cluster allowlist and auth
upload_file FS Write to ./data/uploads/, reference from spark_submit

Environment variables

Variable Default Required Description
LISTEN_ADDR :8080 no HTTP listen address
DATA_DIR ./data no SQLite, uploads, and log root
ADMIN_TOKENS yes Comma-separated tokens for /admin/*
AGENT_TOKEN yes Token for /mcp requests
HTTP_CLIENT_TIMEOUT 30s no Timeout for fetch_url/RM Tool HTTP calls
MAX_RESPONSE_BYTES 1048576 (1 MiB) no HTTP response truncation limit
SPARK_SUBMIT_TIMEOUT 60s no spark-submit process timeout
LOG_DIR ./data/logs no Log root directory
LOG_LEVEL info no debug, info, warn, or error
LOG_FORMAT text no text for terminal, json for log files
ANALYZER_DATA_SKEW_RATIO 3.0 no Data-skew rule threshold (max/min ratio)
ANALYZER_GC_PRESSURE_RATIO 0.1 no GC-pressure rule threshold (GC/CPU ratio)
ANALYZER_BOTTLENECK_SHUFFLE_GB 50 no Bottleneck rule threshold (shuffle GB)

Admin API

All endpoints require Authorization: Bearer <admin_token>.

Method Path Description
GET /admin/clusters List all clusters
POST /admin/clusters Create a cluster
GET /admin/clusters/:id Get one cluster
PUT /admin/clusters/:id Update a cluster
DELETE /admin/clusters/:id Delete a cluster
GET /admin/audit?limit=100 Query audit log

Create a cluster:

curl -sS -X POST \\
  -H "Authorization: Bearer ${ADMIN_TOKEN}" \\
  -H "Content-Type: application/json" \\
  -d '{
    "id": "prod",
    "name": "prod",
    "rm_url": "http://rm.example.com:8088",
    "shs_url": "http://shs.example.com:18080",
    "spark_submit_execute_bin": "/opt/spark/bin/spark-submit",
    "is_active": true,
    "auth_type": "simple",
    "auth_username": "yarn",
    "rate_limit_per_min": 10,
    "url_allowlist": ["rm.example.com:8088", "shs.example.com:18080"]
  }' \\
  "http://127.0.0.1:${LISTEN_ADDR:-:8080}/admin/clusters"

Note: auth_password is not accepted via JSON (json:"-"). Set it through a dedicated password endpoint or seed the database directly.

Security model

Three lines of defense:

  1. Token auth - ADMIN_TOKENS protects /admin/*; AGENT_TOKEN protects /mcp.
  2. SSRF guard - Every outbound URL must match the cluster's url_allowlist, with private-IP CIDR blacklist (incl. 169.254.0.0/16 AWS/GCP metadata).
  3. Path allowlist - upload_file writes only to ./data/uploads/, rejects absolute paths, .., and non-[a-zA-Z0-9._-] filenames.

Additional guarantees:

  • spark_submit runs the cluster's binary via exec.Command(name, args...) — slice form, never sh -c. No shell metacharacter interpretation.
  • auth_password is tagged json:"-"; never serialized in responses, never accepted from JSON request bodies.
  • Cross-host redirects (RM → NM 307) preserve the Authorization header through DoWithRedirect only when the destination host is in url_allowlist.
  • Per-Tool log files are created with mode 0600 and live under ./data/logs/tools/.

Development

go build ./...
go test ./...
go vet ./...

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