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Gram DocumentationGram FunctionsUsing the Functions Framework

Using the Functions Framework

Overview

The Gram Functions Framework provides a streamlined way to build MCP tools using TypeScript. It handles the MCP protocol implementation while letting you focus on your tool logic.

Choosing the Gram Framework

Function structure

Every Gram Function follows this basic structure:

gram.ts
import { Gram } from "@gram-ai/functions";
import * as z from "zod/mini";
 
const gram = new Gram().tool({
  name: "add",
  description: "Add two numbers together",
  inputSchema: { a: z.number(), b: z.number() },
  async execute(ctx, input) {
    return ctx.json({sum: input.a + input.b});
  },
});
 
export default gram;

Environment Variables

With Gram functions you can specify credentials or envrionment variable values that will need to be provided to your tool runner. These can be provided either by end user set MCP headers or with stored Gram environments.

const gram = new Gram({
  envSchema: {
    BASE_URL: z.string().check(z.url()),
  },
}).tool({
  name: "api_call",
  inputSchema: { endpoint: z.string() },
  async execute(ctx, input) {
    const baseURL = ctx.env?.["BASE_URL"];
    // Use baseURL...
  },
});

Using Fetch

With Gram functions you can make requests to downstream APIs and respond with the result.

const gram = new Gram()
  .tool({
    name: "spacex-ships",
    description: "Get the latest SpaceX ship list",
    inputSchema: {},
    async execute(ctx) {
      return fetch("https://api.spacexdata.com/v3/ships");
    },
  });

Next steps

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