Generate embeddings for text data (requires pgvector extension and API integration)
AI agents invoke vector_embed to trigger actions in Postgres Mcp Legacy. 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.
This tool executes an external API call to generate embeddings and likely writes/stores them in a pgvector-enabled PostgreSQL database. It spans Write and Execute categories; since it triggers external operations (API integration) whose effects depend on arguments, Execute is the most appropriate classification.
From the tool's definition 'Generate embeddings for text data (requires pgvector extension and API integration)' — triggers external API calls and database operations via pgvector extension
Documented attack patterns abuse exactly the kind of access vector_embed gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Postgres Mcp Legacy, and nothing reaches the server without passing your rules. This is the rule we recommend for vector_embed:
{
"version": "1",
"default": "deny",
"tools": {
"vector_embed": {
"limits": [
{
"counter": "vector_embed_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}vector_embed 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.
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Generate embeddings for text data (requires pgvector extension and API integration). It is categorised as a Execute tool in the Postgres Mcp Legacy MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Postgres Mcp Legacy MCP server in PolicyLayer and add a rule for vector_embed: 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 Postgres Mcp Legacy. Nothing to install.
vector_embed 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 vector_embed 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 vector_embed. 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.
vector_embed is provided by the Postgres Mcp Legacy MCP server (neverinfamous/postgres-mcp-legacy). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Postgres Mcp Legacy, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
60 Postgres Mcp Legacy tools catalogued and risk-classified — across an index of 43,000+ MCP servers.