{"id":"ray-mcp-server","name":"ray-mcp-server","homepage":"https://pypi.org/project/ray-mcp-server/","repo_url":"https://github.com/pradeepiyer/ray-mcp.git","category":"devtools","subcategories":[],"tags":["mcp","ray","distributed-compute","agent-tools","tooling"],"what_it_does":"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.","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"],"best_when":null,"avoid_when":null,"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"],"af_score":28.2,"security_score":29.5,"reliability_score":20.0,"package_type":"mcp_server","discovery_source":["pypi"],"priority":"low","status":"evaluated","version_evaluated":null,"last_evaluated":"2026-04-04T21:46:10.737590+00:00","interface":{"has_rest_api":false,"has_graphql":false,"has_grpc":false,"has_mcp_server":true,"mcp_server_url":null,"has_sdk":false,"sdk_languages":[],"openapi_spec_url":null,"webhooks":false},"auth":{"methods":[],"oauth":false,"scopes":false,"notes":null},"pricing":{"model":null,"free_tier_exists":false,"free_tier_limits":null,"paid_tiers":[],"requires_credit_card":false,"estimated_workload_costs":null,"notes":null},"requirements":{"requires_signup":false,"requires_credit_card":false,"domain_verification":false,"data_residency":[],"compliance":[],"min_contract":null},"agent_readiness":{"af_score":28.2,"security_score":29.5,"reliability_score":20.0,"mcp_server_quality":40.0,"documentation_accuracy":30.0,"error_message_quality":0.0,"error_message_notes":null,"auth_complexity":20.0,"rate_limit_clarity":10.0,"tls_enforcement":50.0,"auth_strength":20.0,"scope_granularity":20.0,"dependency_hygiene":30.0,"secret_handling":30.0,"security_notes":"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.","uptime_documented":0.0,"version_stability":30.0,"breaking_changes_history":30.0,"error_recovery":20.0,"idempotency_support":"false","idempotency_notes":null,"pagination_style":"none","retry_guidance_documented":false,"known_agent_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"]}}