synesis-graph: Universal Graph Pipeline

Transform your qualitative research into a living, navigable Knowledge Graph ready for AI (GraphRAG).

Language: English | Portugues

Documentation: Synesis Language Docs

This repository contains the official pipeline from the Synesis language to graph representations. It acts as a bridge between structured human analysis (.syn files) and computational intelligence, enabling MCP Agents and Data Science algorithms to interact with your research.

Three backends ship today — Neo4j and ArcadeDB (property graphs) and HTML (self-contained interactive visualization). All are built on the same BackendAdapter contract, so support for further graph databases can be added without touching the pipeline.

Choosing a backend

Both database backends produce the same graph from the same project: on the FACE/UFMG corpus every structural count matches (concepts, items, sources and all relationship types). They differ in how the advanced metrics are scoped — see Graph Metrics.

Highlights

• Zero-IO / Direct Link: Uses the synesis.load() API to compile the project in memory and sync directly to the database. No intermediate JSON/CSV files.
• Universal & Agnostic: Does not depend on fixed rules (like "Factors" or "Dimensions"). The script reads your Template (.synt) and creates the graph structure dynamically.
• Automatic Metrics: Calculates network metrics at two levels:
  • Native Metrics: Always available via pure Cypher.
  • GDS Metrics: Advanced algorithms when the Graph Data Science plugin is installed.
• Full Traceability: Every node and edge maintains origin metadata (source_file, line, column), ensuring scientific auditability.

Architecture

The pipeline follows the "Research as Code" flow:

1. Input: Plain text files (.syn, .syno, .synt, .synp) defined by the Synesis language.
2. Compilation: The compiler validates syntax and semantics in real-time.
3. Dynamic Modeling: The script translates Template definitions into graph structures.
4. Persistence: Data is injected into Neo4j via atomic transactions.
5. Analytics: Graph metrics are calculated and stored in nodes.

Data Modeling: Template → Graph

The pipeline automatically translates field types defined in your Template (.synt) to structures in the Neo4j graph. This translation is dynamic and does not depend on specific field names.

Mapping Table

Base Nodes (Always Created)

Translation Example

Template:

FIELD category TYPE CODE
    SCOPE ITEM
END FIELD

FIELD theme TYPE TOPIC
    SCOPE ONTOLOGY
END FIELD

Resulting Graph:

(:Item)-[:MENTIONS]->(:Category)-[:GROUPED_BY]->(:Theme)

Graph Metrics

The pipeline automatically calculates network metrics that enrich the analysis. Metrics are divided into two levels:

Native Metrics (Always Available)

Calculated via pure Cypher, without external dependencies.

Concept Nodes (CODE)

Taxonomy Nodes (TOPIC, ASPECT, DIMENSION)

Source Nodes

Advanced Metrics

The same three metrics are produced by both database backends, from different engines:

The scores are not directly comparable between the two. Neo4j's GDS projects only the concept subgraph (concepts and their RELATES_TO edges), while ArcadeDB's algo.* procedures run over the whole graph and accept no scope filter — so MENTIONS, GROUPED_BY and the other edges contribute as well. Concepts cited by many items rank higher under ArcadeDB. On the FACE/UFMG corpus the two top-10 PageRank lists overlap by 6 of 10 entries. Both are valid centralities; they answer slightly different questions.

Values are written only onto concept nodes in both cases. The pipeline prints this caveat on every ArcadeDB export.

Neo4j (GDS)

When the Neo4j Graph Data Science plugin is installed, the pipeline calculates advanced network metrics:

Graph Projection Strategies

GDS metrics calculation automatically adapts to template type:

Note: If GDS is not installed, the pipeline displays a warning and continues normally with native metrics.

ArcadeDB (built-in)

ArcadeDB ships a native algorithm library, so no plugin is involved and there is no degraded path: pagerank, betweenness and community are always computed. Graph projection strategies do not apply — the algorithms always see the full graph.

Installation

Requires Python 3.10+ and synesis ≥ 0.10.0.

# Clone the repository
git clone https://github.com/synesis-lang/synesis-graph.git
cd synesis-graph

# Install (editable) with the graph backends you need
pip install -e ".[neo4j]"

# The ArcadeDB and HTML backends need no extra — they use only the standard library
pip install -e .

Compatibility matrix

GDS Plugin (Optional)

For advanced metrics, install the Neo4j Graph Data Science:

# Neo4j Desktop: Plugins → Install Graph Data Science Library
# Neo4j Server: Download JAR and add to plugins/ directory

Configuration

Create a config.toml file in the root with the credentials of the backend you use:

[neo4j]
uri = "bolt://localhost:7687"  # Or your Neo4j Aura URI
user = "neo4j"
password = "your_secret_password"
database = "neo4j"             # Optional, default is 'neo4j'

[arcadedb]
uri = "http://localhost:2480"  # HTTP endpoint — NOT a bolt:// URL
user = "root"
password = "your_secret_password"
# database = "my_corpus"       # Optional, derived from the project name
# fulltext_analyzer = "brazilian"

Both blocks may coexist; each backend reads only its own. See config.toml.example for every option.

Usage

Pick a backend and point it at the Synesis project file (.synp):

# Sync to Neo4j
synesis-graph neo4j --project ./my-project/analysis.synp

# Sync to ArcadeDB
synesis-graph arcadedb --project ./my-project/analysis.synp

# Render a self-contained interactive HTML graph
synesis-graph html --project ./my-project/analysis.synp --output graph.html

# See every backend and its options
synesis-graph --help

What happens during execution?

1. Compilation: The Synesis compiler validates your code. Syntax errors are displayed and the process stops (the destination is not touched).
2. Connection: If compilation succeeds, the pipeline connects to the selected backend.
3. Constraints: Uniqueness rules are applied based on the Template.
4. Synchronization: Data is injected (Concepts, Citations, Sources, Relationships).
5. Native Metrics: Calculated via pure Cypher.
6. Advanced Metrics: GDS on Neo4j (with a warning if the plugin is absent), built-in algo.* on ArcadeDB (always available).

Resulting Graph Structure

Main Relationships

Cypher Query Example

// Find the 10 most central concepts
MATCH (c:Concept)
WHERE c.pagerank IS NOT NULL
RETURN c.name, c.pagerank, c.mention_count, c.community
ORDER BY c.pagerank DESC
LIMIT 10

// Explore thematic communities
MATCH (c:Concept)
WHERE c.community = 42
RETURN c.name, c.pagerank
ORDER BY c.pagerank DESC

MCP Agent Integration (AI)

Once your data is in Neo4j, you can use the Neo4j MCP Server to allow LLMs (like Claude Desktop or Cursor) to converse with your research.

Quick Installation

# Install uv (if needed)
pip install uv

Claude Desktop Configuration

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "synesis-neo4j": {
      "command": "uvx",
      "args": ["mcp-neo4j-cypher@0.5.2", "--read-only"],
      "env": {
        "NEO4J_URI": "bolt://localhost:7687",
        "NEO4J_USERNAME": "neo4j",
        "NEO4J_PASSWORD": "your_password",
        "NEO4J_DATABASE": "database_name"
      }
    }
  }
}

File location:

• Windows: %APPDATA%\Claude\claude_desktop_config.json
• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Question Examples

Complete Documentation

See the mcp/ folder for:

• SETUP.en.md - Complete configuration guide
• QUERIES_REFERENCE.en.md - Cypher query reference
• Configuration templates for single and multiple databases

Flow Diagram

graph TD
    %% Styles
    classDef files fill:#e1f5fe,stroke:#01579b,stroke-width:2px;
    classDef engine fill:#fff3e0,stroke:#ff6f00,stroke-width:2px;
    classDef data fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px;
    classDef graphDb fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px;
    classDef agent fill:#212121,stroke:#000,stroke-width:2px,color:#fff;

    subgraph "1. Input: Research as Code"
        SYN[Annotated Corpus<br/>.syn]:::files
        SYNO[Ontology<br/>.syno]:::files
        SYNP[Project<br/>.synp]:::files
        SYNT[Template<br/>.synt]:::files
    end

    subgraph "2. Synesis Engine"
        COMPILER{{synesis.load}}:::engine
        VALIDATOR(Semantic Validation):::engine

        SYNP --> COMPILER
        SYN --> COMPILER
        SYNO --> COMPILER
        SYNT --> COMPILER
        COMPILER --> VALIDATOR
    end

    subgraph "3. Structured Data"
        JSON[Canonical Object<br/>Traceable]:::data
        SCHEMA[Dynamic Schema<br/>from Template]:::data

        VALIDATOR -->|Success| JSON
        SYNT -.->|Defines| SCHEMA
    end

    subgraph "4. Knowledge Graph"
        NEO4J[(Neo4j)]:::graphDb
        NATIVE[Native Metrics<br/>Cypher]:::graphDb
        GDS[GDS Metrics<br/>Optional]:::graphDb

        JSON & SCHEMA -->|Sync| NEO4J
        NEO4J --> NATIVE
        NATIVE --> GDS

        subgraph "Metrics"
            DEG[Degree<br/>Centrality]
            PR[PageRank<br/>Relevance]
            BC[Betweenness<br/>Bridges]
            COM[Louvain<br/>Communities]
        end
        NATIVE -.-> DEG
        GDS -.-> PR & BC & COM
    end

    subgraph "5. Intelligent Consumption"
        MCP[MCP Agent]:::agent
        LLM[LLMs / Claude]:::agent

        NEO4J <-->|GraphRAG| MCP
        MCP <-->|Queries| LLM
    end

License

This program is distributed under the GNU Affero General Public License, version 3 only (AGPL-3.0-only), with the Synesis Data-Output Exception — see LICENSE and LICENSE.exception.

SPDX identifier: AGPL-3.0-only AND LicenseRef-Synesis-data-output-exception

The graphs you generate are yours. Exported artifacts — Cypher scripts, Neo4j databases, and the standalone HTML visualization — are not covered by the AGPL and carry no copyleft obligation toward Synesis.

This matters especially here: the generated HTML embeds Synesis's own JavaScript and CSS so the visualization can render standalone. That embedded material is Synesis Runtime Material under the Exception, and it does not place the generated file under the AGPL. You may publish, sell, or license the HTML you generate under any terms you choose.

The AGPL applies to synesis-graph itself: if you modify it and distribute it, or run it as a network service, you must share your changes under the AGPL.

Releases published before this change remain available under the MIT license they were issued under.

This license grants no rights to the "Synesis" name or logo.

Part of the Synesis Language ecosystem.