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Verg API

Public, agent-native access to curated convergence intelligence. No authentication required. Rate-limited to 60 requests/minute per IP.

Quick Start

# Get current convergence patterns
curl https://verg.dev/api/patterns?limit=5
# Get top thought leaders
curl https://verg.dev/api/leaders?limit=10
# OpenAPI 3.0 spec (machine-readable)
curl https://verg.dev/api/openapi.json

Endpoints

GET/api/patterns

Returns current convergence patterns with full provenance. Each pattern includes the CI score, independence verification, token bake cost, and links back to raw sources.

Query parameters:
  • limit — max patterns (default 10)
  • min_ci — minimum CI score filter (0-1)
Response shape:
{
  "meta": { "total_patterns": 12, "generated_at": "..." },
  "patterns": [
    {
      "id": "cp_e40f7a3c",
      "label": "AI agents need human supervision",
      "ci_score": 0.26,
      "independence_score": 0.68,
      "token_cost": { "raw_tokens": 18421, "curated_tokens": 723, "savings_percent": 96.1 },
      "signal_quality": { "independence": "high", "platforms": [...] },
      "sources": [...]
    }
  ]
}
GET/api/leaders

Thought leaders ranked by contribution score — not follower count. Each leader has originality, independence, centrality, and source depth metrics.

Query parameters:
  • limit — max leaders (default 10)
  • type — filter: architect, philosopher, amplifier, contrarian, bridge
  • min_score — minimum leader score
GET/api/openapi.json

Full OpenAPI 3.0 specification. Machine-readable — drop it into Claude Code, Cursor, or any agent framework that supports OpenAPI tool discovery.

POST/api/feedback

Submit feedback on a pattern or source. Agents and humans can both provide feedback to improve source quality scoring and pattern validation over time.

Key Concepts

CI Score (Convergence Intelligence)

Strength of convergence (0-1). Measures how many independent sources align and how closely their framing matches. 0.7+ is strong convergence.

Independence Score

Measured via social graph analysis (PageRank, Louvain communities). 0.7+ = strong cross-community convergence. Below 0.5 = potential echo chamber. Note: captures surface-level dependence (citations, affiliations) but not hidden common causes.

Token Bake

The processing cost of each insight. Raw source tokens in → curated structured artifact tokens out. Both numbers are measured from disk every run (chars/4 of the actual content), not estimated. Typical compression sits in the ~95-97% range — querying Verg returns the structured intelligence object instead of forcing the agent to process every contributing source itself. See /protocol#token-bake for the live measured numbers.

Leader Contribution

Scored on 4 dimensions: originality (novel ideas), independence (not echoing), centrality (pattern involvement), source depth (deep work vs shallow takes). NOT based on follower count.

Agent Integration

MCP Server

For Claude Code, Cursor, Windsurf, and other MCP-compatible tools, Verg offers a native MCP server with 5 tools: verg_patterns, verg_leaders, verg_emerging, verg_search, verg_predictions.

Discovery