io.github.HISHAMJOTTERREV/sentiogate-mcp · v1.0.1 · ai-and-media
SentioGate FinOps & LLM Router is healthy: it completed an MCP handshake in 1172 ms and exposes 6 tools.
BYOK AI router & FinOps control plane: audit token waste, check tool safety, and rank models.
Endpoint: https://api.sentiogate.dev/v1/mcp (streamable-http)
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| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 6 |
| Latency | 1172 ms |
| Last checked (UTC) | 2026-11-08T22:10:17.976Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-11-08T22:10:17.976Z | Healthy | 1172 |
sentiogate_audit_waste | Analyze past LLM request logs (raw JSON/JSONL/CSV or array of message turns) to detect cost waste, unnecessary context bloat, prompt-cache opportunities, and achievable savings with SentioGate. |
sentiogate_get_finops_ledger | Fetch real-time SentioGate BYOK FinOps metrics: measured spend by provider, prompt-cache USD savings, active sessions, and remaining 5-hour Community Pool quota. |
sentiogate_recommend_model | Recommend the optimal model and provider fallback chain for a given coding or agent task based on real-time task difficulty, live catalog pricing, and measured latency. |
sentiogate_guard_check | Pre-flight check tool calls, terminal commands, or conversation history against SentioGate Armor security rules (credential leakage, destructive rm, pipe-to-shell, git force-push, and runaway tool loops). |
sentiogate_optimize_payload | Preview and simulate context compaction and tool-output trimming on an array of conversation messages without executing upstream model inference. |
sentiogate_delegate_prompt | Route a chat completion sub-task through SentioGate (using model "auto" or a pinned provider/model) or enqueue it on the background batch queue. |