Insider Radar
REMOTE · INSIDER-RADAR-AGENT.INSIDER-RADAR-AGENT.WORKERS.DEV · 2 COMPONENTS · SCANNED AUG 21
Lab telemetry market: 25 x402 USDC-paid tools — leaderboard, KOL signals, outcomes, more.
How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →
Endpoint Security46
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- Authorisation not fully verified: no authorisation is required to call this server, and 27 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe. See how to fix → View diagnostics → Unverified
- HTTPS check failed: the endpoint is reachable over plaintext HTTP. See how to fix → View diagnostics → Fail
- HSTS check failed: the Strict-Transport-Security header is absent. See how to fix → View diagnostics → Fail
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
Schema Quality & AI Usability70
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 2125 tokens (~78/item across 27 items; 27 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
- Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.
remote · insider-radar-agent.insider-radar-agent.workers.dev
claude mcp add --transport http mypocketsmells-insider-radar https://insider-radar-agent.insider-radar-agent.workers.dev/sse
[mcp_servers.mypocketsmells-insider-radar] url = "https://insider-radar-agent.insider-radar-agent.workers.dev/sse"
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"mypocketsmells-insider-radar": {
"type": "remote",
"url": "https://insider-radar-agent.insider-radar-agent.workers.dev/sse",
"enabled": true
}
}
} openclaw mcp add mypocketsmells-insider-radar --url https://insider-radar-agent.insider-radar-agent.workers.dev/sse --transport streamable-http
mcp_servers:
mypocketsmells-insider-radar:
url: "https://insider-radar-agent.insider-radar-agent.workers.dev/sse" {
"mcpServers": {
"mypocketsmells-insider-radar": {
"type": "http",
"url": "https://insider-radar-agent.insider-radar-agent.workers.dev/sse"
}
}
} The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 20 Aug 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.
- 18 Aug 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 13 to 17. That category is still filling its 30-day observation window: 4 days of observed history at the previous scan, 5 at this one. The score rises as the window fills, whether or not the server changes.
- 16 Aug 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.
- 14 Aug 26 +1
- Stability: unverified → 0.03 ▲ functional
- 13 Aug 26 51
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 21 Aug 2026 · Probed https://insider-radar-agent.insider-radar-agent.workers.dev/sse
TLS valid
Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=insider-radar-agent.workers.dev | CN=WE1,O=Google Trust Services,C=US | 12 Aug 2026 | 10 Nov 2026 | ECDSA 256 | ECDSA-SHA256 | 9dc8c8c6c3b10a170e701ed5bfc31942 |
| SANs: insider-radar-agent.workers.dev, *.insider-radar-agent.workers.dev | ||||||
| CN=WE1,O=Google Trust Services,C=US (CA) | CN=GTS Root R4,O=Google Trust Services LLC,C=US | 13 Dec 2023 | 20 Feb 2029 | ECDSA 256 | ECDSA-SHA384 | 7ff31977972c224a76155d13b6d685e3 |
| CN=GTS Root R4,O=Google Trust Services LLC,C=US (CA) | CN=GlobalSign Root CA,OU=Root CA,O=GlobalSign nv-sa,C=BE | 15 Nov 2023 | 28 Jan 2028 | ECDSA 384 | SHA256-RSA | 7fe530bf331343bedd821610493d8a1b |
DNSSEC insecure
Validation of insider-radar-agent.insider-radar-agent.workers.dev. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| dev. | present | 60074 | 8 | Verified |
| workers.dev. | absent | Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation |
Authentication No authorisation required
The endpoint answered without asking for a token. Anyone who knows the URL can reach it.
| Result | No authorisation required |
|---|---|
| HTTP status | 404 |
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| sse | https://insider-radar-agent.insider-radar-agent.workers.dev/sse | Verified | 200 | |
| http (plaintext) | http://insider-radar-agent.insider-radar-agent.workers.dev/sse | Served over HTTP | 200 |
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.
alerts ~69
Recent lab alerts (drawdowns, retirements, anomalies). Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
alpha_track ~89
Daily equity/PnL histories for the lab's edge-protected bots under stable anonymous handles — real performance, withheld identities; track any handle across snapshots. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
arena ~29
Fleet-wide arena summary of the paper-trading lab (bot counts, venues, aggregate equity). Free teaser.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
calibration ~67
Forecast calibration by venue/category — predicted vs realized. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
congress_tape ~83
Parsed House/Senate PTR trades: member, ticker, type, amounts, filing lag (last 1000). Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
creators ~88
Pump.fun deployer index built forward by our launch listener: 900+ creator wallets with launch histories, venue-aware rug counts, first/last seen. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
crowding ~71
Exposure crowding: where the fleet's directional risk is concentrated. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
divergences ~76
Cross-venue probability divergences (e.g. Kalshi vs Polymarket gaps). Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
fleet_ledger ~86
Fleet-wide daily P&L ledger: totals, venue splits, per-day rows, tape reconciliation — the transparency companion to alpha_track. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
insider_plans ~87
10b5-1 plan detection per insider filing — was the buy pre-scheduled? Per-accession tags plus aggregate plan rates. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
insider_tape ~88
Parsed SEC Form-4 insider buys, newest first: roles, titles, shares, price, value, disclosure lag (last 1000). Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
kol_events ~84
Narrated detector event stream: meta-signals, distribution flips, known-rugger callouts (last 2000 events). Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
kol_froth ~84
Memecoin froth gauge, current level plus full history: human buys/hour, danger share, distribution events, percentile. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
kol_outcomes ~99
Forward-marked signal outcomes WITH a matched control arm: rug rates, checkpoint returns (15m/1h/6h/24h) by risk level and confluence — honesty-graded. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
kol_signals_delayed ~86
Same KOL confluence feed as kol_signals_live with every row at least 45 minutes old — the evaluation tier. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
kol_signals_live ~92
Live KOL confluence buy/exit signals (≤15 min old): distinct human buyers, strength, rug-risk callouts, momentum — the actionable tier. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
kol_stats ~85
Per-wallet outcome statistics for ~300 tracked memecoin KOL wallets — our computed win rates and PnL distributions over observed trades. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
leaderboard ~71
Ranked bot leaderboard with eff_n and the luck-ceiling honesty note. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
optimizer ~65
Optimizer status and recent parameter decisions. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
radar_status ~28
Service status: snapshot freshness, product catalog with per-call prices, and the honesty disclaimer. Free.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
research_pack ~91
Seven research panels in one call: family correlation + effective-n, edge calibration, insider event study, regime joins, econ calendar, weekly digest, daily alpha cards. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
signals ~68
Current signal feed headlines from the lab's signal bus. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
smart_holdings ~84
13F institutional holdings rollup: top-held names, filer roster, per-ticker holder counts (top 300). Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
snipe_outcomes ~86
Launch-snipe paper ledger with a randomized control arm: detect latency, entry efficiency, checkpoint marks per snipe. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
sol_depth ~97
Recorded Kalshi SOL-market L2 depth (top-5 levels per side), previous-day and older only (T+1) — we recorded it live; Kalshi publishes no historical depth. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
solscout_verdicts ~86
Copy-gradeability verdicts for Solana memecoin wallets: composite scores, consistency, retirement calls (candidate lists withheld). Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
wire_clusters ~86
Cross-source evidence clusters joining price anomalies to specific SEC filings (Form 4 accessions, URLs) — graded, windowed, cited. Paper-trading lab telemetry; All figures are simulated paper dollars from a research lab — not investment advice, not live trading, no real positions. Ranked returns are dominated by luck until effective bet counts (eff_n), calibration and crowding say otherwise.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.