Is OpenChainBench MCP server safe?
Yes, with the usual care.
Safe to use. Minor gaps such as a missing repository or slower maintenance.
No critical or high findings in the latest scan.
How OpenChainBench compares
Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 81/100
- higher than 62% of 48,255 servers
- Tools that change things
- 0%
- typical: 0%. Fewer write tools means less an agent can break
- Uptime
- 100%
- of our recent checks; the typical remote server answers 100%
What its tools let an agent do: 3 read
Public scan report
scanner v0.1.9 · 2026-09-25 · same rubric, same numbers if you re-run it
1 low
- –Code scanremote-only server, no package to scann/a
- Live reliabilityremote reachable in 572ms20/20
- Tool poisoning3 tool descriptions checked13/15
- Auth qualityopen endpoint, read-only tools10/15
- Maintenancelast push 0 days ago15/15
- Maintainer identitynamespace and repository owner differ3/10
Findings (1)
- lowUnusually long tool description (over 2,000 characters)
poison.long-descriptiontool query_prom: …Direct PromQL passthrough for advanced questions that don't map cleanly to `list_benchmarks` / `get_benchmark`, e.g. "what was Mobula's p50 head-lag yesterday at 14:00 UTC" or "plot bridge fees over the last hour". Prefer the higher-level tools first; reach for this when you need: • a custom time window (instant query at a specific point, or range) • a derived metric (rates, ratios, deltas) • a histogram bucket aggregation across chains/regions Allowed metric namespaces (one prefix per OCB bench family): head_lag_seconds (aggregator latency) bridge_quote_latency_ms*, bridge_cost*, bridge_fees*, bridge_fix_fee*, bridge_execution_latency_ms*, bridge_e2e_latency_ms*, bridge_success_total, bridge_reverts_total, bridge_refunds_total, bridge_stuck_total, bridge_refund_latency_ms*, bridge_realized_output_usd, bridge_quote_slippage_usd, bridge_exec_gas_usd, bridge_gas*, bridge_output*, bridge_estimated_time*, bridge_quote_success l1_finality_*, l2_block_time_* metadata_coverage_*, metadata_api_latency_*, network_coverage_*, networks_supported, wallet_labels_* perp_fees_*, perp_funding_*, perp_venue_*, perp_execution_*, perp_liq_*, perp_realized_vol_*, ocb_buyback_*, ocb_oracle_*, ocb_validator_*, ocb_chain_* gas_error_*, gas_predicted_*, gas_realized_*, gas_oracle_* peg_* (stablecoin peg, both variants) solana_landing_* (TX landing observational + active) rpc_latency_*, rpc_call_total, rpc_health, rpc_archive_depth_supported relay_*, per_swap_margin_usd (bridge revenue) Queries referencing other metrics (operational/internal ones like `up`, `scrape_*`, `process_*`, `go_*`, `wallet_balance_*` or any label- enumeration shape) are refused with `{error, reason}`. Example: instant p50 over 1h for Mobula head-lag on Base: query_prom({ query: "quantile_over_time(0.5, head_lag_seconds{aggregator=\"mobula\",chain=\"base\"}[1h]) * 1000" }) Example: 7-day sparkline of average bridge fees: query_prom({ query: "avg_over_time(bridge_fees_percent[1d])", windowSec: 604800, steps: 168 }) Returns: `{ query, value }` for instant queries, `{ query, windowSec, series }` for range.…
Overall 81/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON
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