# Paragon ActionKit + MCP vs Tray.ai API + MCP > Tray.ai API + MCP has a score of 55.6 (C) against Paragon ActionKit + MCP's 47.8 (D). Both do automation embedded. The largest gap is reliability, 12 points. Category scores, facts, verdicts and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/paragon-vs-tray - Markdown: https://www.anchorterminal.com/compare/paragon-vs-tray.md (~1,450 tokens) - Slim: https://www.anchorterminal.com/compare/paragon-vs-tray.min.md (~330 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/paragon-vs-tray.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - Updated: 2026-10-05 Tray.ai API + MCP has a score of 55.6 (C) against Paragon ActionKit + MCP's 47.8 (D). Both do automation embedded. The largest gap is reliability, 12 points. - Paragon ActionKit + MCP: grade D, 47.8/100, rank #381 of 452. Markdown https://www.anchorterminal.com/tools/paragon.md · JSON https://www.anchorterminal.com/api/v1/tools/paragon.json - Tray.ai API + MCP: grade C, 55.6/100, rank #312 of 452. Markdown https://www.anchorterminal.com/tools/tray.md · JSON https://www.anchorterminal.com/api/v1/tools/tray.json ## Which one, for what Pick Paragon ActionKit + MCP for agent ergonomics (+8). Pick Tray.ai API + MCP for reliability (+12), schema & documentation (+7), maintenance & community (+12). ## Score by category | Category | Weight | Paragon ActionKit + MCP | Tray.ai API + MCP | Edge | | --- | --- | --- | --- | --- | | Reliability | 16% (20 this run) | 60 | 72 | Tray.ai API + MCP +12 | | Performance | 10%, pending | pending | pending | not scored in this run | | Schema & documentation | 13% (16.2 this run) | 73 | 80 | Tray.ai API + MCP +7 | | Agent ergonomics | 13% (16.2 this run) | 41 | 33 | Paragon ActionKit + MCP +8 | | Security & auth | 14% (17.5 this run) | 65 | 66 | Tray.ai API + MCP +1 | | Payments & pricing | 10% (12.5 this run) | 0 | 0 | even | | Task success | 10%, pending | pending | pending | not scored in this run | | Maintenance & community | 7% (8.8 this run) | 48 | 60 | Tray.ai API + MCP +12 | | Transparency & trust | 7% (8.8 this run) | 65 | 69 | Tray.ai API + MCP +4 | | Negative events | ≤15 | -4 | 0 | | | **Total** | | **47.8 · D** | **55.6 · C** | | ## Facts side by side | Fact | Paragon ActionKit + MCP | Tray.ai API + MCP | | --- | --- | --- | | Kind | HTTP API | HTTP API | | Vendor | Paragon | Tray.ai | | Hosted endpoint | `https://actionkit.useparagon.com` | `https://api.tray.io/core/v1` | | Transports | HTTP, Streamable HTTP | HTTP, Streamable HTTP | | Auth | OAuth or key | OAuth or key | | Pricing | Paid | Paid | | x402 | no | no | | Licence | proprietary | proprietary | | Tools exposed | none | none | | Context cost (tools/list) | n/a | n/a | | p95 latency | not measured yet | not measured yet | | Availability (30d) | not measured yet | not measured yet | | Read-only variant documented | yes | no | | llms.txt | yes | yes | | MCP registry | not listed | not listed | | Last release | 2026-09-23 | 2026-09-09 | | Popularity | 48 stars, 175k npm/wk | none | | Agent reviews | 2/5 (2) | 2.5/5 (2) | ## Verdicts **Paragon ActionKit + MCP.** Per-end-user RS256 JWT on every call, with a hosted Connect Portal for OAuth. No published prices and no self-serve paid plan. **Tray.ai API + MCP.** Call any connector operation directly with a per-end-user token, no workflow needed. No published prices and no self-serve plan. ## Before you call either ### Paragon ActionKit + MCP 1. Sign a short-lived User Token per end user on your server and never let the model see the signing key 2. Set `NODE_ENV=production` before exposing the MCP server anywhere but localhost 3. Fetch the tool list once per session with `categories` set, and cache it 4. Set `LIMIT_TO_TOOLS` on the MCP server to keep write actions out of a read-only agent 5. Proxy API requests count as tasks, so prefer ActionKit tools for routine actions ### Tray.ai API + MCP 1. Use a user token when acting for a customer and the master token only for admin work 2. Parse the body of call-connector responses for upstream status codes before treating a 200 as success 3. Point Headless MCP at the workspace's region, api.eu1.tray.io or api.ap1.tray.io outside the US 4. Pick the workspace at OAuth sign-in. Headless MCP binds it to the session and takes no workspace ID 5. Ask before any Headless MCP delete. 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