Calculate PageRank scores for nodes (simplified implementation)
AI agents use neo4j.page_rank to create or update resources in Neo4j MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Neo4j MCP Server environment.
An AI agent can call neo4j.page_rank faster than any human can review — one bad instruction and it creates or modifies resources in Neo4j MCP Server by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
Calculate PageRank scores for nodes (simplified implementation). It is categorised as a Write tool in the Neo4j MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Neo4j MCP Server MCP server in PolicyLayer and add a rule for neo4j.page_rank: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Neo4j MCP Server. Nothing to install.
neo4j.page_rank is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the neo4j.page_rank rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for neo4j.page_rank. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
neo4j.page_rank is provided by the Neo4j MCP Server MCP server (vpro1032/neo4j-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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