ray-mcp-server

ray-mcp-server is an MCP server (Model Context Protocol) intended to expose Ray-related functionality to MCP-compatible AI agents/tools. The package name strongly suggests it wraps Ray capabilities behind MCP tool interfaces for agent-driven orchestration.

Evaluated Apr 04, 2026 (27d ago)
Homepage ↗ Repo ↗ DevTools mcp ray distributed-compute agent-tools tooling
⚙ Agent Friendliness
28
/ 100
Can an agent use this?
🔒 Security
30
/ 100
Is it safe for agents?
⚡ Reliability
20
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
40
Documentation
30
Error Messages
0
Auth Simplicity
20
Rate Limits
10

🔒 Security

TLS Enforcement
50
Auth Strength
20
Scope Granularity
20
Dep. Hygiene
30
Secret Handling
30

No README/repo contents were provided here to confirm authentication, authorization scopes, TLS requirements, or how secrets are handled. MCP servers often run as local processes or internal services; security should be verified (e.g., network binding, authN/Z, least privilege, logging redaction) before use in multi-user or internet-exposed environments.

⚡ Reliability

Uptime/SLA
0
Version Stability
30
Breaking Changes
30
Error Recovery
20
AF Security Reliability

Use Cases

  • • Let an AI agent trigger Ray tasks/actors and query Ray state via MCP tools
  • • Build agent workflows that monitor/inspect distributed Ray executions
  • • Integrate Ray into agentic systems using MCP rather than bespoke APIs

Not For

  • • Direct public HTTP API consumption without MCP support
  • • Production-grade multi-tenant SaaS usage where strong auth/scoping and operational controls are required (not evidenced here)
  • • Environments that cannot run the MCP server process or cannot reach it

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
No
Webhooks
No

Authentication

OAuth: No Scopes: No

Pricing

Free tier: No
Requires CC: No

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • ⚠ Agents may unintentionally trigger expensive Ray jobs/actors without guardrails
  • ⚠ Without clear tool semantics and idempotency, retries can duplicate work
  • ⚠ If the MCP server exposes broad Ray control primitives, least-privilege constraints may be necessary at deployment time

Alternatives

Ray SDK integration directly from the application (Python/Java/JS) instead of MCP Custom REST/gRPC wrapper around Ray APIs Other MCP servers that provide higher-level orchestration around distributed compute

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Scores are editorial opinions as of 2026-04-04.

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