Vercel AI SDK

pnpm add ai @ai-sdk/mcp @ai-sdk/anthropic zod
pnpm add -D tsx typescript @types/node
npm pkg set type=module

export NIMA_API_KEY="nima_…"
export ANTHROPIC_API_KEY="sk-ant-…"

import { pathToFileURL } from 'node:url';
import { createMCPClient, type MCPClient } from '@ai-sdk/mcp';

const NIMA_MCP_URL = 'https://mcp.getnima.io/mcp';

export async function connectNima(): Promise<MCPClient> {
  const apiKey = process.env.NIMA_API_KEY;
  if (!apiKey) {
    throw new Error('Set NIMA_API_KEY to a personal nima API key (nima_…).');
  }

  return createMCPClient({
    transport: {
      type: 'http',
      url: NIMA_MCP_URL,
      headers: { Authorization: `Bearer ${apiKey}` },
    },
  });
}

async function main(): Promise<void> {
  let client: MCPClient | undefined;
  try {
    client = await connectNima();
    const tools = await client.tools();
    console.log(Object.keys(tools).sort().join('\n'));
  } finally {
    await client?.close();
  }
}

if (import.meta.url === pathToFileURL(process.argv[1]).href) {
  main().catch((error) => {
    console.error(error);
    process.exitCode = 1;
  });
}

npx tsx connect.ts

npx tsx agent.ts "The weekly CSV import stalls on large files. What should I change?"

-> ask_knowledge_graph {"q":"why does the weekly CSV import stall on large files","limit":5}
-> search_code {"q":"where is the CSV import chunk size set","limit":5}

  Knowledge graph results for: "why does the weekly CSV import stall on large files"

  ### Streaming importer (feature) [implemented] · id: 9d2f4c61-0b7e-4a3d-8f15-6c2e9a7b3d40
  References: 6 | Similarity: 0.742
  Summary: Chunked CSV import that replaced the legacy importer.
  Facts:
    - shipped_at: 2026-03-19 (source: PR:5c7d9e13-2a4b-4e6f-8c1d-3b5a7e9f0c22, learned 2026-03-19)
  Relations:
    - requested → Northwind (customer) — "asked twice in Q1 for imports above 50 MB"

{
  "query": "where is the CSV import chunk size set",
  "repositories": [
    {
      "id": "3f8b0a41-6c2d-4f19-9ab7-15d0e2c7a884",
      "repoFullName": "acme/orbit",
      "indexStatus": "ready",
      "lastCommitSha": "b41c9de2f7a1c05b8e3d6410a9f2c7d3e5b81a60"
    }
  ],
  "droppedRepositories": [],
  "results": [
    {
      "filePath": "src/import/stream.ts",
      "score": 0.79,
      "match": "semantic",
      "summary": "Reads an uploaded CSV in fixed-size chunks.",
      "symbols": [
        { "name": "readChunks", "kind": "function", "lineStart": 18, "lineEnd": 64 }
      ]
    }
  ]
}

import { pathToFileURL } from 'node:url';
import { anthropic } from '@ai-sdk/anthropic';
import { createMCPClient, type MCPClient } from '@ai-sdk/mcp';
import { generateText, hasToolCall, isStepCount } from 'ai';

async function main(finding: string): Promise<void> {
  const apiKey = process.env.NIMA_API_KEY;
  if (!apiKey) {
    throw new Error('Set NIMA_API_KEY to a personal nima API key (nima_…).');
  }

  let client: MCPClient | undefined;
  try {
    // No maxRetries here: a retried create_signal files a second signal.
    client = await createMCPClient({
      transport: {
        type: 'http',
        url: 'https://mcp.getnima.io/mcp',
        headers: { Authorization: `Bearer ${apiKey}` },
      },
    });

    const { create_signal } = await client.tools();
    if (!create_signal) {
      throw new Error('nima did not advertise create_signal.');
    }

    const { steps } = await generateText({
      model: anthropic('claude-opus-5-5'),
      instructions:
        'File exactly one signal with create_signal. Put the finding in content, in plain words. ' +
        'Set sourceLabel to "vercel ai sdk agent". Fill stakeholders and productAreas only when the finding names them.',
      tools: { create_signal },
      stopWhen: [hasToolCall('create_signal'), isStepCount(3)],
      prompt: finding,
    });

    const calls = steps.flatMap((step) => step.toolCalls);
    console.log(JSON.stringify(calls.map((call) => call.input), null, 2));
  } finally {
    await client?.close();
  }
}

if (import.meta.url === pathToFileURL(process.argv[1]).href) {
  const finding =
    process.argv.slice(2).join(' ') ||
    'On the Northwind call: the weekly CSV import dies around 40k rows with a 504. They are splitting the file by hand.';
  main(finding).catch((error) => {
    console.error(error);
    process.exitCode = 1;
  });
}

[
  {
    "content": "On the Northwind call: the weekly CSV import dies around 40k rows with a 504. They are splitting the file by hand.",
    "sourceLabel": "vercel ai sdk agent",
    "stakeholders": ["Northwind"],
    "productAreas": ["import"]
  }
]

import { pathToFileURL } from 'node:url';
import { anthropic } from '@ai-sdk/anthropic';
import { generateText, isStepCount, tool } from 'ai';
import { z } from 'zod';

const NIMA_API = 'https://api.getnima.io';

function nimaHeaders(): Record<string, string> {
  const apiKey = process.env.NIMA_API_KEY;
  if (!apiKey) {
    throw new Error('Set NIMA_API_KEY to a personal nima API key (nima_…).');
  }
  return { Authorization: `Bearer ${apiKey}` };
}

async function nimaGet(path: string, params: Record<string, string>): Promise<string> {
  const url = new URL(path, NIMA_API);
  for (const [key, value] of Object.entries(params)) url.searchParams.set(key, value);
  const response = await fetch(url, { headers: nimaHeaders() });
  const body = await response.text();
  if (!response.ok) {
    return `nima answered ${response.status} (X-Request-Id ${response.headers.get('x-request-id')}): ${body.slice(0, 500)}`;
  }
  return body;
}

const tools = {
  ask_knowledge_graph: tool({
    description: 'Ask what the workspace knows about the product: who asked, why, what was decided. Returns markdown.',
    inputSchema: z.object({
      q: z.string().min(2).max(500).describe('A plain English question'),
      limit: z.number().int().min(1).max(20).optional(),
    }),
    execute: async ({ q, limit }) =>
      nimaGet('/v1/knowledge-graph/ask', { q, ...(limit ? { limit: String(limit) } : {}) }),
  }),
  search_code: tool({
    description: 'Find code in the indexed repositories: files, summaries, symbols, line ranges, and the indexed commit.',
    inputSchema: z.object({
      q: z.string().min(2).max(300).describe('Where is X, or a symbol name'),
      limit: z.number().int().min(1).max(20).optional(),
    }),
    execute: async ({ q, limit }) =>
      nimaGet('/v1/code-intel/search', { q, ...(limit ? { limit: String(limit) } : {}) }),
  }),
};

async function main(task: string): Promise<void> {
  const { text } = await generateText({
    model: anthropic('claude-opus-5-5'),
    instructions: 'Call ask_knowledge_graph, then search_code, before you answer. Quote what they return.',
    tools,
    stopWhen: isStepCount(6),
    prompt: task,
  });
  console.log(text);
}

if (import.meta.url === pathToFileURL(process.argv[1]).href) {
  const task = process.argv.slice(2).join(' ') || 'The weekly CSV import stalls on large files. What should I change?';
  main(task).catch((error) => {
    console.error(error);
    process.exitCode = 1;
  });
}

curl -s -X POST "https://api.getnima.io/v1/signals" \
  -H "Authorization: Bearer $NIMA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "On the Northwind call: the weekly CSV import dies around 40k rows with a 504. They are splitting the file by hand.",
    "sourceLabel": "vercel ai sdk agent",
    "stakeholders": ["Northwind"],
    "productAreas": ["import"]
  }'