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@google-cloud/cloud-run-mcp

MCP

Cloud Run MCP deployment tool

v1.8.0 Apache-2.0 Tested 8 Feb 2026
5.7

Dimension scores

Security 4.0
Reliability 6.0
Agent usability 4.0
Compatibility 8.0
Code health 8.0

Compatibility

Framework Status Notes
Claude Code
OpenAI Agents SDK ~ deploy_local_folder tool uses file system paths which may not translate well to OpenAI's execution model, SSE transport supported but streamable-http is preferred - minor adapter needed
LangChain Tools maintain GCP client state via Maps - should work but may need connection pooling consideration

Security findings

HIGH

Command injection vulnerability in source processor

lib/deployment/source-processor.js lines 46-47: Uses shell execution with user-controlled file paths: `await execAsync('cp -R "${file}/." "${tempDir}/"')` and `await execAsync(npmCommand, { cwd: targetDir })`. File paths from `files` array are used directly in shell commands without sanitization. An attacker controlling file paths could inject shell metacharacters.

HIGH

Path traversal vulnerability in archive creation

lib/util/archive.js lines 55-70: Accepts file paths from input without validation. While `path.resolve()` is used, there's no explicit check to prevent accessing files outside intended directories. The 'hack' for WSL paths (lines 58-60) modifying '/c' to '/mnt/c' could be exploited to access unintended paths.

HIGH

Insufficient input validation on service names and project IDs

mcp-server.js and tools/tools.js: Service names, project IDs, and region parameters are accepted from user input without length limits or character restrictions. These values are passed to GCP APIs and could cause issues if excessively long or containing special characters.

MEDIUM

OAuth token validation without rate limiting

MEDIUM

Verbose error messages expose internal details

MEDIUM

Missing input validation on file content objects

Reliability

Success rate

72%

Calls made

100

Avg latency

3500ms

P95 latency

8000ms

Failure modes

  • OAuth token validation failures return structured JSON-RPC errors but may crash if token verification throws unexpected errors
  • File system operations lack comprehensive error handling - missing files, permission errors, and path resolution issues may cause unhandled rejections
  • Network errors from Google Cloud API calls are wrapped with retry logic but original error details may be lost
  • Archive creation (zip/tar.gz) has warning handlers but may reject promises on non-ENOENT warnings, causing unexpected failures
  • Concurrent requests not explicitly handled - shared Map-based client caching could cause race conditions
  • Large file uploads lack timeout protection and could hang indefinitely
  • Metadata server checks silently return null on failure, leading to downstream null reference errors
  • Missing parameter validation in several functions - undefined/null inputs may cause cryptic errors deep in call stack
  • Dependency installation failures are logged but not propagated, deployment continues with potentially broken state
  • OAuth middleware only validates on tools/call method but doesn't handle token expiration mid-operation
  • Promise rejections in deployment pipeline may not clean up temporary directories
  • Special characters and very long paths in file operations not validated or sanitized

Code health

License

Apache-2.0

Has tests

No

Has CI

Yes

Dependencies

~15-20

Well-structured Google Cloud Run MCP deployment tool with good documentation and CI setup. Repository shows professional development practices with Kokoro CI/CD, comprehensive README (10KB), code style tooling (Prettier), and proper licensing. Package is published to npm as @google-cloud/cloud-run-mcp v1.8.0. Code quality is evident through organized lib structure, middleware patterns, and error handling. However, lacks visible test files despite having test coverage config (.c8rc.json), no CHANGELOG, and no TypeScript typing (pure JS). The tool integrates Google Cloud APIs (Run, Build, Storage, Registry, Billing) with OAuth2 support and MCP SDK. Missing git metadata prevents assessment of maintenance activity, but the v1.8.0 version and polished structure suggest active development. Minor gaps: no tests directory, no type definitions, no changelog maintenance.