This record as markdown: /tools/io-github-devopam-mcpg/cluster-vectors.md
What cluster_vectors does on Mcpg
AI agents invoke cluster_vectors to trigger actions in Mcpg. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why cluster_vectors is rated High
The name 'cluster_vectors' suggests a vector clustering operation, likely involving computation over stored vector data. Given the PostgreSQL context and sibling tools related to HNSW, distance metrics, and reranking, this likely executes a clustering algorithm (e.g., k-means) on vector embeddings.
From the tool's definition Tool name 'cluster_vectors'; description is empty and uninformative.
Attacks that exploit this kind of access
The rule that runs cluster_vectors safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcpg, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For cluster_vectors, this is the rule to start with:
cluster_vectors stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcpg, apply this rule, and every cluster_vectors call is checked against it from then on.
Questions about cluster_vectors
cluster_vectors is a execute tool on the Mcpg MCP server. It is categorised as a Execute tool in the Mcpg MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mcpg MCP server in PolicyLayer and add a rule for cluster_vectors: 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 Mcpg. Nothing to install.
cluster_vectors is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the cluster_vectors 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 cluster_vectors. 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.
cluster_vectors is provided by the Mcpg MCP server (pypi:mcpg). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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