MCP MeasureMCP Measure

index observed

Insider Radar

Lab telemetry market: 25 x402 USDC-paid tools — leaderboard, KOL signals, outcomes, more.

Should I use this

Quality & Safety

B
Description quality
100%
Schema completeness
30%
Naming quality
81%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~3,149Tokens (tool definitions)
~255 BTypical response size
Significant attention impact (2.46% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "insider-radar": {
      "url": "https://insider-radar-agent.insider-radar-agent.workers.dev/mcp"
    }
  }
}

Remote endpoints

https://insider-radar-agent.insider-radar-agent.workers.dev/mcpstreamable-http
https://insider-radar-agent.insider-radar-agent.workers.dev/ssesse

What it can do

Tool inventory

Tools (27)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
⚪radar_status

Service status: snapshot freshness, product catalog with per-call prices, and the honesty disclaimer. Free.

Input Schema

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
⚪arena

Fleet-wide arena summary of the paper-trading lab (bot counts, venues, aggregate equity). Free teaser.

Input Schema

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢leaderboard

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢signals

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢alerts

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢calibration

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢divergences

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢crowding

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢optimizer

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢creators

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢kol_stats

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢alpha_track

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢sol_depth

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢kol_signals_live

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢kol_outcomes

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢snipe_outcomes

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢wire_clusters

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢solscout_verdicts

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢insider_plans

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢research_pack

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢kol_events

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢fleet_ledger

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢kol_signals_delayed

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢kol_froth

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢smart_holdings

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢insider_tape

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢congress_tape

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

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Recommended Prompts

find_specific
Find [specific item] using Insider Radar
Expected tools: research_pack
search_research
Search for information about [topic] using Insider Radar
Expected tools: research_pack

Community

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Evidence

Recent observations

verifiedversion not recorded27 tools
verifiedversion not recorded27 tools
verifiedversion not recorded27 tools
verifiedversion not recorded27 tools