{"id":"30064d42-b689-46e0-bd82-4c42212f381b","entityType":"agent","slug":"tescolopio-openclaw-neo4j-skill","name":"neo4j","canonicalUrl":"https://www.xpersona.co/agent/tescolopio-openclaw-neo4j-skill","canonicalPath":"/agent/tescolopio-openclaw-neo4j-skill","generatedAt":"2026-10-10T06:21:02.236Z","source":"GITHUB_OPENCLEW","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-04-15T05:21:22.124Z","emptyReason":null},"description":"Interact with Neo4j graph database for knowledge graphs, Cypher queries, and AGI relational reasoning via MCP. --- name: neo4j description: Interact with Neo4j graph database for knowledge graphs, Cypher queries, and AGI relational reasoning via MCP. metadata: {\"openclaw\":{\"requires\":{\"bins\":[\"python3\",\"docker\"]},\"install\":[{\"id\":\"neo4j-driver\",\"kind\":\"pip\",\"package\":\"neo4j\",\"bins\":[],\"label\":\"Install Neo4j Python driver\"}],\"env\":[\"NEO4J_URI\",\"NEO4J_USER\",\"NEO4J_PASSWORD\"]}} --- Neo4j Graph Skill for AGI What I do This skill","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. 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It supports symbolic queries, graph updates, and computational algorithms like centrality.\n\n## When to use me\nUse for AGI tasks requiring graph-based memory: pattern matching, multi-hop inference, influence analysis. Do not use for destructive operations unless explicitly allowed (e.g., updates are read-only by default).\n\n## Security Notes\n- **Root Risk:** Runs in Docker container with read-only filesystem, non-root user.\n- **Keys Risk:** Credentials via environment vars (NEO4J_*); never log or expose.\n- **Agency Risk:** Least privilege—queries only; updates require explicit approval.\n\n## Setup\n1. Run Neo4j: `docker run -d --name neo4j -p 7474:7474 -p 7687:7687 -e NEO4J_AUTH=$NEO4J_USER/$NEO4J_PASSWORD neo4j:latest`\n2. Install deps: `pip install neo4j`\n3. Set env: `export NEO4J_URI=bolt://localhost:7687 NEO4J_USER=neo4j NEO4J_PASSWORD=password`\n\n## MCP Server\nSave as `neo4j_mcp_server.py` (run in container for security):\n```python\nimport asyncio\nimport json\nimport os\nimport sys\nfrom neo4j import GraphDatabase\n\nuri = os.getenv('NEO4J_URI', 'bolt://localhost:7687')\nuser = os.getenv('NEO4J_USER', 'neo4j')\npassword = os.getenv('NEO4J_PASSWORD', 'password')\n\ndriver = GraphDatabase.driver(uri, auth=(user, password))\n\nasync def handle_request(request):\n    method = request.get('method')\n    params = request.get('params', {})\n    \n    if method == 'tools/list':\n        return {\n            'tools': [\n                {\n                    'name': 'query_graph',\n                    'description': 'Run Cypher query for symbolic reasoning (read-only)',\n                    'inputSchema': {'type': 'object', 'properties': {'query': {'type': 'string'}}}\n                },\n                {\n                    'name': 'update_graph',\n                    'description': 'Update graph (requires approval; use sparingly)',\n                    'inputSchema': {'type': 'object', 'properties': {'cypher': {'type': 'string'}}}\n                },\n                {\n                    'name': 'compute_centrality',\n                    'description': 'Compute PageRank for influence analysis',\n                    'inputSchema': {'type': 'object', 'properties': {'label': {'type': 'string'}, 'relationship': {'type': 'string'}}}\n                },\n                {\n                    'name': 'visualize_graph',\n                    'description': 'Generate Mermaid config for graph visualization',\n                    'inputSchema': {'type': 'object', 'properties': {'query': {'type': 'string'}}}\n                }\n            ]\n        }\n    elif method == 'tools/call':\n        tool_name = params['name']\n        args = params['arguments']\n        \n        with driver.session() as session:\n            if tool_name == 'query_graph':\n                result = session.run(args['query'])\n                records = [dict(record) for record in result]\n                return {'content': [{'type': 'text', 'text': json.dumps(records)}]}\n            elif tool_name == 'update_graph':\n                # Add approval check here\n                session.run(args['cypher'])\n                return {'content': [{'type': 'text', 'text': 'Graph updated'}]}\n            elif tool_name == 'compute_centrality':\n                cypher = f'CALL gds.pageRank.stream(\"{args[\"label\"]}\", \"{args[\"relationship\"]}\") YIELD nodeId, score RETURN gds.util.asNode(nodeId).name AS name, score ORDER BY score DESC'\n                result = session.run(cypher)\n                records = [dict(record) for record in result]\n                return {'content': [{'type': 'text', 'text': json.dumps(records)}]}\n            elif tool_name == 'visualize_graph':\n                # Generate Mermaid (simplified)\n                result = session.run(args['query'])\n                mermaid = \"graph TD\\n\"\n                for record in result:\n                    if 'n' in record and 'm' in record:\n                        mermaid += f\"{record['n']} --> {record['m']}\\n\"\n                return {'content': [{'type': 'text', 'text': mermaid}]}\n    \n    return {'error': 'Unknown method'}\n\nasync def main():\n    while True:\n        line = await asyncio.get_event_loop().run_in_executor(None, sys.stdin.readline)\n        if not line:\n            break\n        request = json.loads(line.strip())\n        response = await handle_request(request)\n        response['jsonrpc'] = '2.0'\n        response['id'] = request.get('id')\n        print(json.dumps(response), flush=True)\n\nasyncio.run(main())\n```\n\nRun securely: `docker run --rm -e NEO4J_* -v $(pwd):/app python:3.9-slim /app/neo4j_mcp_server.py`\n\n## Packaging\n- **Docker Image:** Build with `Dockerfile` for containerized execution.\n- 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