Username Profanity Screening

What it grounds

Give enterprise agents username moderation through the same data layer, flagging inappropriate handles on demand per check.

Ways to ground with it

Check before you act

Let an agent call Username Profanity Screening to confirm an input is real and safe before it writes a record, sends a message, or completes a task — grounding the decision in a verifiable check.

Guardrail an automated workflow

Wire usernameprofanity into an agent pipeline so risky inputs are flagged and traced, not passed through on the model's hunch.

Auditable validation

Each verdict the agent relies on carries Username Profanity Screening as its source, so a reviewer can see exactly what was checked.

Connect over MCP

Point your agent framework at the VerveContext endpoint. Every enabled source — this one included — becomes a tool the model can call. No per-source plumbing.

context.json

{
  "mcpServers": {
    "vervecontext": {
      "url": "https://api.vervecontext.com/v1/mcp",
      "headers": { "x-api-key": "vc_live_••••" }
    }
  }
}

# “usernameprofanity” is now a tool your agent can call

What it returns

Each call returns structured fields your agent can read.

username
isProfane

Username Profanity Screening, answered

How to ground an agent in it over MCP.

How do I give my agent Username Profanity Screening?

Enable it on VerveContext and point your agent framework at the VerveContext MCP endpoint. Username Profanity Screening then appears to the model as a tool named usernameprofanity, which it calls when a task needs it — no per-source plumbing.

Which agents and frameworks can use it?

Any MCP client — Claude, Cursor, LangChain, and custom agents all speak the Model Context Protocol. Username Profanity Screening is exposed as a standard tool, so nothing source-specific is required.

Can the agent cite Username Profanity Screening?

Username Profanity Screening is a capability rather than a factual source, so it isn't something to "cite" — but it runs on the same real-data layer, over the same MCP endpoint and key as every grounding source.

How many credits does a Username Profanity Screening call cost?

Each call costs 1 credit. Scoped keys let you grant an agent only the sources it should reach, and usage logs show exactly what was pulled to ground each answer.

How current is the data?

Username Profanity Screening is served live from APIVerve's production data engine and pulled at the moment the agent calls it, so answers reflect the world now rather than the model's training cutoff.

Where does the data come from, and what shows on my bill?

VerveContext runs on APIVerve, our production data engine; Username Profanity Screening is one of 300+ sources on the same key. Invoices and card statements show APIVERVE.

Ground alongside

Browse all sources

Check before you act

Guardrail an automated workflow

Auditable validation

Username Profanity Screening, answered

Ground your agents in Username Profanity Screening. Connect over MCP, enable the source, and every answer carries its receipts.

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