# ResearchGravity

> Metaventions AI Research Framework — Multi-tier signal capture for frontier intelligence. Architected Intelligence.

- **Type:** MCP server
- **Install:** `agentstack add mcp-dicoangelo-researchgravity`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Dicoangelo](https://agentstack.voostack.com/s/dicoangelo)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [Dicoangelo](https://github.com/Dicoangelo)
- **Source:** https://github.com/Dicoangelo/ResearchGravity
- **Website:** https://metaventionsai.com

## Install

```sh
agentstack add mcp-dicoangelo-researchgravity
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

Frontier intelligence for meta-invention. Research that compounds.

  "Let the invention be hidden in your vision"

  
  
  
  

  
  
  
  

  
  
  

  

---

## Why • What's New • Architecture • Quick Start • Auto-Capture • Sources • Contact

---

## Proof Deck — See It Work

  

  9-slide interactive proof: real DB stats, EvidencedFinding schema, 3-stream oracle critique, and a live pipeline demo that writes real findings to antigravity.db.

  Open Interactive Deck

---

## What's New in v6.1 — Security & Reliability (January 2026)

**Production-hardened API with enterprise security.**

| Feature | Description |
|---------|-------------|
| **🔐 JWT Authentication** | Token-based auth with `/api/auth/token` endpoint |
| **⏱️ Rate Limiting** | slowapi integration (10/min search, 30/min write) |
| **🛡️ Input Validation** | Path traversal prevention, session ID sanitization |
| **📝 Structured Logging** | JSON/console formats with request context |
| **🔄 Dead-Letter Queue** | Failed writes queued for retry with exponential backoff |
| **⚡ Async Cohere** | Non-blocking embedding calls via `asyncio.to_thread` |
| **🔒 Connection Pool** | Semaphore-guarded SQLite pool (race condition fix) |

### Authentication

```bash
# Get JWT token
curl -X POST http://localhost:3847/api/auth/token \
  -H "Content-Type: application/json" \
  -d '{"client_id": "my-app", "scope": "write"}'

# Use token
curl -H "Authorization: Bearer " http://localhost:3847/api/auth/me

# Or use API key
curl -H "X-API-Key: " http://localhost:3847/api/v2/stats
```

### Environment Variables

```bash
export RG_SECRET_KEY=$(python -c "import secrets; print(secrets.token_hex(32))")
export RG_API_KEY="your-service-api-key"
export RG_LOG_LEVEL="INFO"  # DEBUG, INFO, WARNING, ERROR
export RG_LOG_JSON="true"   # JSON format for production
```

---

## What's New in v6.0 — Interactive Research Platform (January 2026)

**From manual workflow to intelligent auto-capture.** 3x faster research sessions with real-time URL capture.

| Feature | Description |
|---------|-------------|
| **🎮 Interactive REPL** | Real-time research CLI with Rich terminal UI |
| **🔄 Auto-Capture V2** | Automatic URL/finding extraction from Claude sessions (+70% capture rate) |
| **🧠 Intelligence Layer** | CLI + API + REPL access to meta-learning predictions |
| **💾 sqlite-vec Storage** | Local vector storage with FTS fallback (no external dependencies) |
| **👁️ File Watcher** | Implicit session creation from Claude activity |
| **📊 Dual-Write Engine** | Qdrant + sqlite-vec with automatic failover |

### Interactive REPL

```bash
python3 scripts/session/repl.py

# Commands:
rg> start "multi-agent orchestration"   # Initialize session
rg> url https://arxiv.org/...           # Log URL (auto-classify)
rg> finding "Key insight about..."      # Capture finding
rg> predict                             # Session quality prediction
rg> search "consensus algorithms"       # Semantic search past sessions
rg> archive                             # Finalize session
```

### Auto-Capture V2

```bash
python3 scripts/session/auto_capture_v2.py scan         # Scan last 24 hours
python3 scripts/session/auto_capture_v2.py scan --hours 48
python3 scripts/session/auto_capture_v2.py status       # Show capture stats
```

### Intelligence CLI

```bash
python3 scripts/prediction/intelligence.py predict "task"   # Session quality prediction
python3 scripts/prediction/intelligence.py optimal-time     # Best hour for deep work
python3 scripts/prediction/intelligence.py errors "context" # Likely errors + prevention
python3 scripts/prediction/intelligence.py patterns         # Session patterns
```

### Intelligence API

| Endpoint | Method | Description |
|----------|--------|-------------|
| `/api/v2/intelligence/status` | GET | System capabilities |
| `/api/v2/intelligence/predict` | POST | Unified prediction |
| `/api/v2/intelligence/patterns` | GET | Session patterns |
| `/api/v2/intelligence/errors` | POST | Likely errors |
| `/api/v2/intelligence/feedback` | POST | Outcome feedback |

### File Watcher

```bash
python3 scripts/session/watcher.py daemon   # Start as background daemon
python3 scripts/session/watcher.py status   # Check daemon status
python3 scripts/session/watcher.py stop     # Stop daemon
```

### Storage Modes

```
Priority: Qdrant → sqlite-vec → FTS fallback
- Qdrant: Full semantic search (requires server)
- sqlite-vec: Single-file vectors (offline capable)
- FTS: Full-text search fallback (always available)
```

### Embedding Providers (SOTA 2026)

```
Priority: Cohere v4 → Cohere v3 → SBERT offline

Cohere embed-v4.0 (default):
- Multimodal (text + images)
- 128k context window
- Matryoshka dimensions: 256, 512, 1024, 1536

Dimension Options:
- 1536d: Maximum quality
- 1024d: Balanced (default)
- 512d:  50% storage savings
- 256d:  83% storage savings

Fallback Chain:
- Cohere v4 → Cohere v3 → SBERT (all-MiniLM-L6-v2)
```

Auto-switches on API failure. No manual configuration needed.

---

## What's New in v5.0 — Chief of Staff (January 2026)

**The AI Second Brain is now complete.** Full infrastructure for sovereign knowledge management.

| Feature | Description |
|---------|-------------|
| **🔮 Meta-Learning Engine** | Predictive session intelligence from 666+ outcomes, 1,014 cognitive states |
| **🏛️ Storage Triad** | SQLite (WAL mode, FTS5) + Qdrant (semantic search) |
| **⚖️ Writer-Critic System** | 3 critics validate archives, evidence, and context packs |
| **🕸️ Graph Intelligence** | 11,579 nodes, 13,744 edges — concept relationships & lineage |
| **🔌 REST API** | 22 endpoints on port 3847 for cross-app integration |
| **📊 Oracle Consensus** | Multi-stream validation for high-stakes outputs |
| **🎯 Evidence Layer** | Citations, confidence scoring, source validation |

### Chief of Staff Architecture

```
┌──────────────────────────────────────────────────────────────────────────────┐
│                         CHIEF OF STAFF INFRASTRUCTURE                         │
├──────────────────────────────────────────────────────────────────────────────┤
│                                                                               │
│  ┌─────────────┐    ┌─────────────┐    ┌─────────────┐    ┌─────────────┐   │
│  │   CAPTURE   │───▶│  STORAGE    │───▶│ INTELLIGENCE│───▶│  RETRIEVAL  │   │
│  │             │    │   TRIAD     │    │             │    │     API     │   │
│  │ Sessions    │    │             │    │ Writer      │    │             │   │
│  │ URLs        │    │ SQLite      │    │ Critic      │    │ REST /api/* │   │
│  │ Findings    │    │ Qdrant      │    │ Oracle      │    │ Graph /v2   │   │
│  │ Transcripts │    │ Graph       │    │ Evidence    │    │ SDK         │   │
│  └─────────────┘    └─────────────┘    └─────────────┘    └─────────────┘   │
│                                                                               │
│  ┌────────────────────────────────────────────────────────────────────────┐  │
│  │                           GRAPH INTELLIGENCE                            │  │
│  │                                                                         │  │
│  │   Sessions ──contains──▶ Findings ──cites──▶ Papers                    │  │
│  │      │                      │                   │                       │  │
│  │      └──────enables─────────┴────derives_from───┘                       │  │
│  │                                                                         │  │
│  │   11,579 Nodes  •  13,744 Edges  •  Concept Clusters  •  Lineage       │  │
│  └────────────────────────────────────────────────────────────────────────┘  │
│                                                                               │
└──────────────────────────────────────────────────────────────────────────────┘
```

### v4.0 Features (Still Available)

| Feature | Description |
|---------|-------------|
| **🧠 CPB Module** | Cognitive Precision Bridge — 5-path AI orchestration |
| **🎯 ELITE TIER** | 5-agent ACE consensus, Opus-first routing, 0.75 DQ bar |
| **📊 DQ Scoring** | Validity (40%) + Specificity (30%) + Correctness (30%) |
| **🔀 Smart Routing** | Auto-select path based on query complexity |

### CPB Execution Paths

```
┌─────────────────────────────────────────────────────────────────────────┐
│                    COGNITIVE PRECISION BRIDGE (CPB)                     │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                         │
│  Query → [Complexity Analysis] → Path Selection → Execution → DQ Score  │
│                                                                         │
│  ┌──────────┬──────────┬──────────┬──────────┬──────────┐              │
│  │  DIRECT  │   RLM    │   ACE    │  HYBRID  │ CASCADE  │              │
│  │  0.7+   │  >0.7    │              │
│  │  Simple  │ Context  │ Consensus│ Combined │ Full     │              │
│  │  ~1s     │  ~5s     │   ~5s    │  ~10s    │  ~15s    │              │
│  └──────────┴──────────┴──────────┴──────────┴──────────┘              │
│                                                                         │
│  5-Agent ACE Ensemble:                                                  │
│  🔬 Analyst | 🤔 Skeptic | 🔄 Synthesizer | 🛠️ Pragmatist | 🔭 Visionary │
│                                                                         │
└─────────────────────────────────────────────────────────────────────────┘
```

### 🆕 CPB Precision Mode v2.0

**Research-grounded answers with 95%+ quality target.** Combines tiered search, grounded generation, and cutting-edge convergence research.

```
┌─────────────────────────────────────────────────────────────────────────┐
│                    PRECISION MODE v2 PIPELINE                           │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                         │
│  Query                                                                  │
│    │                                                                    │
│    ▼ PHASE 1: TIERED SEARCH (ResearchGravity methodology)              │
│    │  ├── Tier 1: arXiv, Labs, Industry News                           │
│    │  ├── Tier 2: GitHub, Benchmarks, Social                           │
│    │  └── Tier 3: Internal learnings (Qdrant)                          │
│    │                                                                    │
│    ▼ PHASE 2: CONTEXT GROUNDING                                        │
│    │  └── Build citation-ready context (agents cite ONLY these)        │
│    │                                                                    │
│    ▼ PHASE 3: GROUNDED CASCADE (7 agents)                              │
│    │  └── 🔬🤔🔄🛠️🔭📚💡 with citation enforcement                      │
│    │                                                                    │
│    ▼ PHASE 4: MAR CONSENSUS (Multi-Agent Reflexion)                    │
│    │  └── ValidityCritic + EvidenceCritic + ActionabilityCritic        │
│    │                                                                    │
│    ▼ PHASE 5: TARGETED REFINEMENT (IMPROVE pattern)                    │
│    │  └── Fix weakest DQ dimension per retry                           │
│    │                                                                    │
│    ▼ PHASE 6: EDITORIAL FRAME                                          │
│    │  └── Extract thesis / gap / innovation direction                  │
│    │                                                                    │
│    ▼ Result (DQ score + verifiable citations)                          │
│                                                                         │
└─────────────────────────────────────────────────────────────────────────┘
```

| Feature | Description |
|---------|-------------|
| **Tiered Search** | arXiv API + GitHub API + Internal Qdrant |
| **Time-Decay Scoring** | Research: 23-day half-life, News: 2-day |
| **Signal Quantification** | Stars, citations, dates extracted |
| **Grounded Generation** | Agents can ONLY cite retrieved sources |
| **MAR Consensus** | 3 persona critics → synthesis (arXiv:2512.20845) |
| **Targeted Refinement** | IMPROVE pattern (arXiv:2502.18530) |

**Usage:**
```bash
python3 -m cpb precision "your research question" --verbose
```

### v3.5 Changelog

| Feature | Description |
|---------|-------------|
| **Precision Bridge Research** | Tesla US20260017019A1 → RLM synthesis methodology |
| **Cognitive Wallet Tracking** | 114 sessions, 2,530 findings, 8,935 URLs, 27M tokens |
| **Deep Dive Workflow** | Multi-paper synthesis with implementation output |
| **Framework Extraction** | COMPRESS → EXPLORE → RECONSTRUCT pattern identified |

### Notable Research Sessions

| Session | Papers | Output |
|---------|--------|--------|
| Chief of Staff Architecture | 374 | Storage Triad, Graph Intelligence, Writer-Critic |
| Tesla Mixed-Precision RoPE | 15 arXiv | `recursiveLanguageModel.ts` implementation |
| Multi-Agent Orchestration | 12 arXiv | ACE/DQ Scoring in OS-App |
| CPB Integration | 8 arXiv | `cpb/` Python module |
| 160+ Papers Meta-Synthesis | 160+ | Unified research index |

## What's New in v3.4

| Feature | Description |
|---------|-------------|
| **Context Prefetcher** | `scripts/session/prefetch.py` — Inject relevant learnings into Claude sessions |
| **Learnings Backfill** | `scripts/backfill/backfill_learnings.py` — Extract learnings from all archived sessions |
| **Memory Injection** | Auto-load project context, papers, and lineage at session start |
| **Shell Integration** | `prefetch`, `prefetch-clip`, `prefetch-inject` shell commands |

### v3.3 Changelog

| Feature | Description |
|---------|-------------|
| **YouTube Research** | `scripts/importers/youtube_channel.py` — Channel analysis and transcript extraction |
| **Enhanced Backfill** | Improved session recovery with better transcript parsing |
| **Ecosystem Sync** | Deeper integration with Agent Core orchestration |

### v3.2 Changelog

| Feature | Description |
|---------|-------------|
| **Auto-Capture** | Sessions automatically tracked — URLs, findings, full transcripts extracted |
| **Lineage Tracking** | Link research sessions to implementation projects |
| **Project Registry** | 4 registered projects with cross-referenced research |
| **Context Loader** | Auto-load project context from any directory |
| **Unified Index** | Cross-reference by paper, topic, or session |
| **Backfill** | Recover research from historical Claude sessions |

---

## Why ResearchGravity?

Traditional research workflows fail at the frontier:

| Problem | Impact |
|---------|--------|
| Single-source blindspots | Missing critical signals |
| No synthesis | Raw links ≠ research |
| No session continuity | Context lost between sessions |
| No quality standard | Inconsistent output |

**ResearchGravity** solves this with:

- **Multi-tier source hierarchy** — Tier 1 (primary), Tier 2 (amplifiers), Tier 3 (context)
- **Cold Start Protocol** — Never lose session context
- **Synthesis workflow** — Thesis → Gap → Innovation Direction
- **Quality checklist** — Consistent Metaventions-grade output

---

## Architecture

  
    
  

View light mode architecture

  
    
  

### Directory Structure

```
ResearchGravity/
│
├── api/                            # REST API Server (v5.0+)
│   ├── server.py                   # FastAPI on port 3847 — 25 endpoints
│   └── routes/                     # API route modules
│
├── capture/                        # Event capture & normalization
├── chrome-extension/               # Browser extension for URL capture
├── cli/                            # CLI Package (v6.0) — REPL commands & UI
│
├── coherence_engine/               # Cross-platform coherence detection
├── cpb/                            # Cognitive Precision Bridge (v4.0)
├── critic/                         # Writer-Cri

…

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [Dicoangelo](https://github.com/Dicoangelo)
- **Source:** [Dicoangelo/ResearchGravity](https://github.com/Dicoangelo/ResearchGravity)
- **License:** MIT
- **Homepage:** https://metaventionsai.com

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** yes
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-dicoangelo-researchgravity
- Seller: https://agentstack.voostack.com/s/dicoangelo
- Browse the marketplace: https://agentstack.voostack.com/browse

---
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