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เปิดPublished by AI Build Infra • Official MCP Identifier: io.github.AI-BuildInfra/proof-graph
Traditional Retrieval-Augmented Generation (RAG) dumps 5,000 to 20,000 unverified tokens of noisy HTML, sidebars, and duplicate paragraphs into LLM prompts. This causes context bloat, higher token costs, latency spikes, and hallucination amplification.
ProofGraph replaces fuzzy text dumping with Minimum Sufficient Context backed by Cryptographic Provenance:
Question ──► Entity Resolution ──► Claim Verification ──► Evidence Ranking ──► Token Optimizer ──► Compact Proof Packet
🎯 ProofGraph retrieves proof, not just text.
npxNo installation required:
npx -y @aibuildinfra/proofgraph
npm install -g @aibuildinfra/proofgraph
Add ProofGraph to your MCP configuration file (claude_desktop_config.json or Antigravity/Cursor MCP settings):
{
"mcpServers": {
"proofgraph": {
"command": "npx",
"args": ["-y", "@aibuildinfra/proofgraph"]
}
}
}
ProofGraph equips AI agents with 12 powerful verification and retrieval tools:
┌────────────────────────────────────────────────────────────────────────────┐
│ PROOFGRAPH MCP TOOLS │
├─────────────────────────┬──────────────────────────────────────────────────┤
│ get_evidence_packet │ Primary retrieval: Minimal sufficient proof │
│ search_entities │ Multi-signal fuzzy & alias entity matching │
│ get_entity │ Canonical record, relationships & Schema.org │
│ verify_claim │ Verify assertions against cryptographic proof │
│ find_evidence │ Token-budgeted evidence extraction for a claim │
│ find_relationships │ 1-hop, 2-hop, 3-hop graph traversal paths │
│ explain_entity │ Concise factual entity profile & key edges │
│ trace_claim │ Step-by-step provenance audit trail │
│ compare_claims │ Impartial discrepancy detection across claims │
│ analyze_web_presence │ Digital footprint analysis across 8 platforms │
│ audit_entity_consistency│ Detect mismatches in names, domains & metadata │
│ export_graph │ Export graph to JSON, JSON-LD, CSV, GraphML │
└─────────────────────────┴──────────────────────────────────────────────────┘
When an AI agent queries:
{
"question": "Is AI Build Infra associated with HumanCraft and ProofGraph?"
}
ProofGraph returns a compact, citation-grounded evidence packet:
{
"entities": [
{
"id": "entity:organization:ai-build-infra",
"name": "AI Build Infra",
"canonical_url": "https://aibuildinfra.com/"
}
],
"claims": [
{
"claim": "AI Build Infra develops MCP servers and open-source agent tooling.",
"status": "supported",
"confidence": 0.98
}
],
"relationships": [
{ "source_id": "entity:organization:ai-build-infra", "relationship": "DEVELOPS", "target_id": "entity:project:proofgraph" },
{ "source_id": "entity:organization:ai-build-infra", "relationship": "DEVELOPS", "target_id": "entity:project:humancraft" }
],
"evidence": [
{
"source": "MCP Registry",
"url": "https://registry.modelcontextprotocol.io/servers/io.github.AI-BuildInfra/humancraft-ui",
"excerpt": "Server identifier io.github.AI-BuildInfra/humancraft-ui registered under AI Build Infra publisher identity.",
"confidence": 0.99
}
],
"provenance": [
{
"source_id": "source:registry:mcp-official",
"content_hash": "10c56a410a5b22e6f3037126be38073b20e950c2ded2ee36815f20072041b889",
"retrieved_at": "2026-09-25T12:00:00Z"
}
],
"metrics": {
"raw_estimated_tokens": 4500,
"returned_tokens": 485,
"compression_ratio": 0.108
}
}
ProofGraph dramatically cuts LLM context consumption without sacrificing retrieval precision:
Run the benchmark locally anytime:
proofgraph benchmark
flowchart TD
Agent[AI Agent / Claude / Antigravity / Cursor] <--> MCP[ProofGraph MCP Protocol Layer]
subgraph Engine [Deterministic Verification Engine]
MCP <--> Optimizer[Token Budget & Deduplication Engine]
MCP <--> Resolver[Multi-Signal Entity Resolver]
MCP <--> Verifier[Claim & Contradiction Verifier]
MCP <--> Traversal[1/2/3 Hop Graph Traversal]
end
subgraph Storage [Cryptographic Provenance Store]
Entities[(Canonical Entities)]
Claims[(Verified Claims)]
Evidence[(Evidence & SHA-256 Hashes)]
Sources[(Authoritative Sources)]
Relationships[(Typed Graph Multigraph)]
end
Engine <--> Storage
subgraph Security [Security & Safety Boundary]
SafeFetch[SSRF Protection\nBlocks RFC1918 & Cloud Metadata]
Robots[Robots.txt & Rate Limiting]
end
Engine <--> Security
# Initialize seed graph
proofgraph init
# Search entities with multi-signal matching
proofgraph search "AI Build Infra"
# Verify a claim with grounded evidence
proofgraph verify "AI Build Infra develops MCP servers"
# Display full cryptographic provenance trail
proofgraph trace "AI Build Infra develops MCP servers"
# Run cross-platform consistency audit
proofgraph audit "AI Build Infra"
# Run AI discoverability checklist
proofgraph discoverability "AI Build Infra"
# Export graph to JSON-LD / CSV / GraphML
proofgraph export jsonld
Explore graph topologies, entities, claims, and audit diagnostics visually:
npm run dashboard
# Open http://localhost:3456
ProofGraph is built under strict open-source safety principles:
127.0.0.0/8, 10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16), link-local IPs, and Cloud Metadata (169.254.169.254, metadata.google.internal).ProofGraph is developed and maintained by AI Build Infra.
Evidence-first entity and knowledge graph MCP server for AI agents to verify claims.
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FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
ProofGraph (Antigravity MCP) ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-08 Evidence-first entity and knowledge graph MCP server for AI agents to verify claims.