Pig Latin Encoding

What it grounds

Give enterprise agents a Pig Latin encoder through the same data layer, transforming text on demand per call.

Ways to ground with it

Normalize before reasoning

Have an agent run text through Pig Latin Encoding to translate, clean, or analyze it in a verifiable step, so downstream reasoning starts from consistent input.

A capability, on the same rails

Expose pig latin encoding to your agents as a tool over the same MCP endpoint and key as every grounding source — no separate integration.

Traceable transforms

Because the transform runs through piglatin, the agent's output can point back to the exact operation that produced it.

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_••••" }
    }
  }
}

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

What it returns

Each call returns structured fields your agent can read.

text
exlcusions

Pig Latin Encoding, answered

How to ground an agent in it over MCP.

How do I give my agent Pig Latin Encoding?

Enable it on VerveContext and point your agent framework at the VerveContext MCP endpoint. Pig Latin Encoding then appears to the model as a tool named piglatin, 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. Pig Latin Encoding is exposed as a standard tool, so nothing source-specific is required.

Can the agent cite Pig Latin Encoding?

Pig Latin Encoding 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 Pig Latin Encoding 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?

Pig Latin Encoding 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; Pig Latin Encoding is one of 300+ sources on the same key. Invoices and card statements show APIVERVE.

Ground alongside

Browse all sources

Normalize before reasoning

A capability, on the same rails

Traceable transforms

Pig Latin Encoding, answered

Ground your agents in Pig Latin Encoding. Connect over MCP, enable the source, and every answer carries its receipts.

Scaling up?